At Vanta, our mission is to help businesses earn and prove trust.We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it.

Vanta’s Corporate Engineering team is the infrastructure layer that keeps 1,500+ people connected, secure, and moving fast. AI is now central to how that happens, and this role leads the team that owns the backbone underneath it.

Corporate Engineering owns the shared AI platform for Vanta’s internal systems: identity and access for AI tools, cost visibility and controls, sanctioned tooling and guardrails, and the enablement that helps people use those tools well. We do not own product AI, which stays with Engineering, and we do not replace the AI work happening inside individual departments. We build the engineering layer that makes all of it safer, cheaper, and better supported.

The company has moved fast. AI assistant use is widespread across every function, MCP infrastructure is live and self-serve company-wide, internal apps ship on a hosted platform, and AI spend has grown to the point where attribution and guardrails genuinely matter. What does not exist yet is a single owner for that platform layer. That is this role.

As Sr. Manager, AI Engineering, you will lead a small, senior team, write the charter for what Corporate Engineering owns versus enables, and build the platform that lets the rest of Vanta adopt AI quickly without accumulating cost, risk, or duplication.

What you’ll do as a Senior Manager, AI Corporate Engineering at Vanta:

• Lead, coach, and grow a senior team spanning platform engineering and technical program management. Set clear direction, hold a high bar, and give the team explicit permission to push back with data.

• Own the AI access layer end to end: identity and authentication for AI tools, connector and integration allowlisting, tiered permissions by function, and guardrails that make adoption safe by default rather than safe by exception.

• Own AI cost engineering. Build attribution down to team and individual, right-size model selection to actual need, make agent and automation spend traceable, and set budget thresholds and alerting in partnership with Finance.

• Own the MCP layer for internal tools end to end, including commissioning, decommissioning, governance, and the downstream impact assessment that has to happen before a migration ships rather than after it breaks.

• Own the paved path for internal applications: a golden-path deployment pattern, sensible defaults including private-by-default, lifecycle and decommissioning policy so unused apps retire themselves, and a build-versus-buy framework that keeps people from rebuilding tools we already own.

• Build the enablement layer that turns adoption into impact: a skills and agent registry that cuts duplication, an evaluation framework for internal AI usage, and technical enablement on sanctioned tools that goes beyond provisioning access.

• Write and hold the charter. Define what Corporate Engineering owns, what it enables, and how work enters the team, then convene the cross-functional forum that keeps departmental AI efforts coordinated rather than duplicated.

• Partner across Engineering, GRC, Security, Data, Finance, and People. Several of the levers this role depends on sit in those organizations, so the job is to coordinate and influence rather than override.

How to be successful in this role:

• Experience standing up an internal AI or developer platform function rather than inheriting a mature one. You have written the charter, defined intake, and built the roadmap from a blank page.

• The ability to hold scope. You can take a commitment that was made without scoping or resourcing, land a bounded first version, and decline the rest without it reading as abdication.

• Fluency in AI cost engineering: usage attribution, model right-sizing, token economics, agent cost traceability, and the difference between a hard limit and a useful guardrail.

• An enablement-first instinct. Your default question is how to make something safe to self-serve. When you do have to decline access, you always explain why and offer an alternative path to the same visibility.

• Hands-on technical depth across LLM platform tooling, agent and MCP architecture, identity and OAuth, CI/CD, and infrastructure as code. Enough to review a design honestly and tell the difference between real risk and reported progress.

• Comfort building for an audience that is no longer only engineers. A growing share of the people shipping internal tools are not developers, and the platform has to work for them without lowering the security bar.

• Data governance fluency in a regulated environment. You know what should never enter a prompt, a repository, or a third-party tool, and you can make that judgment fast without becoming the bottleneck.

• Comfort operating through influence. Product AI, security policy, data platform, and budget authority all sit in partner organizations.

• 8+ years in platform, infrastructure, or systems engineering, including 3+ years managing and developing engineers, ideally at a company that scaled through a significant headcount inflection.

• Must be authorized to work in the U.S. without the need for current or future employer sponsorship.

• Open to using AI to amplify their skills and strengthen their work, demonstrating curiosity, a willingness to learn, and sound judgment in applying AI responsibly to improve efficiency and impact.

What you can expect as a Vanta’n:

• Industry-competitive salary and equity

• Comprehensive medical, dental, and vision coverage, with 100% of employee-only benefit premiums covered for most medical plans

• 16 weeks paid Parental Leave for all new parents

• Health & wellness stipend

• Remote workspace, internet, and cellphone stipend

• Commuter benefits for team members who report to the SF and NYC office

• Family planning benefits

• Matching 401(k) contribution with immediate vesting

• Flexible PTO policy, plus 80 hours of Sick Time

• 11 company-paid holidays

• Virtual team building activities, lunch and learns, and other company-wide events!

• Offices in SF, NYC, London, Dublin, Tel Aviv, and Sydney

To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar-stage growth companies. Final offer amounts are determined by multiple factors and may vary based on candidate location, skills, depth of work experience, and relevant licenses/credentials.

#LI-remote

At Vanta, we are committed to hiring diverse talent of different backgrounds and as such, it is important to us to provide an inclusive work environment for all. We do not discriminate on the basis of race, gender identity, age, religion, sexual orientation, veteran or disability status, or any other protected class. As an equal opportunity employer, we encourage and welcome people of all backgrounds to apply.

About Vanta

We started in 2018, in the wake of several high-profile data breaches. Online security was only becoming more important, but we knew firsthand how hard it could be for fast-growing companies to invest the time and manpower it takes to build a solid security foundation. Vanta was inspired by a vision to restore trust in internet businesses by enabling companies to improve and prove their security. From our early days automating security monitoring for compliance standards like SOC 2, HIPAA and ISO 27001 to creating the world’s leading Trust Management Platform, our vision remains unchanged.

Now more than ever, making security continuous—not just a point-in-time check— is essential. Thousands of companies rely on Vanta to build, maintain and demonstrate their trust— all in a way that’s real-time and transparent.

Referral Instructions

If you are being referred for the role, please contact that person to apply on your behalf.

Harbor Labs is a new team within Harbor focused on solving hard AI implementation problems in the legal market. We have strong hypotheses about what works, but we’re building this like a startup: learning as we go, adjusting direction based on what the market tells us, and staying flexible about how we operate.

We’re looking for a Director of AI Engagements to lead our most important client relationships and set the strategy for how we deploy AI in production. This is a senior role for someone who can sit across the table from a GC or COO, shape the direction of an engagement, and then roll up their sleeves and build alongside the team to deliver it.

This is a leadership role, but not a hands-off one. You’ll own the strategy for your engagements and stay close enough to the work to configure systems, pressure-test outputs, and make the calls that determine whether AI actually sticks in a client’s day-to-day.

What Makes This Different:

Our edge is combining deep legal domain experience with product sensibility and strong engineering. We understand how legal teams actually work, what change management looks like in risk-averse environments, and how to build software that people will use. We also know the common pitfalls of enterprise software in traditionally low-innovation areas like law, and we’re determined to avoid them.

We focus on hard, novel problems where standard platforms fall short. The work is ambiguous, the solutions aren’t obvious, and that’s the point. As a senior leader here, you set the bar for how we approach those problems and how we show up with clients.

What You’ll Do:

• Own the strategy for your engagements. Shape what success looks like with the client’s leadership, define the roadmap, and make the prioritization calls. You’re accountable for the outcome and the relationship, not just the deliverable.
• Lead at the executive level. Be the trusted partner to GCs, COOs, and heads of legal operations. Translate where AI is heading into a concrete plan they can get behind, and bring skeptics along.
• Stay hands-on with the work. Configure systems, structure knowledge sources, write and refine prompts, design test cases, and validate outputs against real data. You lead from inside the work, not above it.
• Set direction for delivery. Define how an engagement is scoped, staffed, and sequenced. Work shoulder-to-shoulder with engineers and delivery leads to turn an ambiguous business problem into a production system.
• Design the operating model, not just the workflow. Figure out how AI changes the way a legal team operates: the processes, the roles, the governance. Redesign how the work gets done, then make the change actually happen.
• Drive architecture and integration decisions. Partner with engineers on how AI fits into client tech stacks: APIs, data flows, security and compliance requirements. Hold the line on what’s production-grade.
• Help build Harbor Labs itself. This is a ground-floor leadership opportunity. You’ll shape how we sell, how we deliver, who we hire, and where we go next.

What We’re Looking For:

• You operate like an owner. You’ve run engagements, programs, or a function end-to-end and been accountable for the result. You set direction when there isn’t one and you don’t wait for permission to fix what’s broken.
• You lead from the front, hands on the work. Seniority hasn’t pulled you away from the details. You’re as comfortable in a configuration screen or a prompt as you are in a boardroom, and you believe the two can’t be separated.
• You’ve delivered real change in how teams work. You understand legal operations, professional services, or a comparable environment, and you’ve redesigned how people actually do their jobs, not just shipped a tool.
• You’re deeply fluent in AI, but not captured by hype. You understand how these systems work in production: RAG architectures, agentic workflows, prompt engineering, evaluation methods. You know how to separate signal from noise when every vendor claims to be the next breakthrough.
• You hold current model-provider credentials. Anthropic Academy certifications (AI Fluency: Framework & Foundations, Claude Code, Building with the Claude API, Model Context Protocol) are a strong plus, and current OpenAI Academy coursework counts too. We treat these as a real signal, not a checkbox: they show you’re building with today’s tools, not describing yesterday’s.
• You’re technical-adjacent and unafraid of it. You don’t need to write Python all day, but you can read an API doc, reason about a system architecture, and have a credible conversation with engineers about tradeoffs.
• You command a room at any level. Executive presentations, working sessions with skeptical users, hard conversations about scope and risk. You build trust fast and hold it under pressure.
• You’re relentlessly practical. You care about what works in production and what changes client behavior, not what sounds impressive in a deck.
• You’re comfortable with ambiguity. Harbor Labs is new and the market is evolving. You’ll set the playbook, not follow one.

Nice to Have:

• Senior experience in legal operations, legal technology, or a transformation/innovation function
• Track record leading client engagements in consulting or professional services
• Experience at a product company (product, solutions, or delivery leadership)
• Hands-on experience with a broad range of AI development tools and LLM APIs

Why Harbor Labs:

We’re a small, senior team working on hard problems with clients who are serious about deploying AI in production. The work is hands-on, the ownership is real, and the leadership you exercise here will directly shape what this team becomes.This is early. You’ll have meaningful input into the strategy, the team, and what Harbor Labs grows into.

How to Apply:

Send us a note about why this role interests you and an engagement or initiative you led that you’re proud of, ideally one where you set the strategy and stayed close to the work. Examples and references matter more to us than a polished resume.

About Us:

Harbor is the preeminent provider of expert services across strategy, legal technology, operations, and intelligence. Our globally integrated team of 900+ strategists, technologists, and specialists navigate alongside our clients – leading law firms, corporations, and their law departments – to provide essential resources and invaluable insights. Anchored in a rich heritage of deep knowledge, steadfast relationships, and mutual respect, our unwavering dedication lies in shaping the future of the legal industry and fostering enduring partnerships within our community and ecosystem.

Harbor is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, marital status, civil union status, national origin, ancestry, age, parental status, disabled status, veteran status, or any other legally protected classification, in accordance with applicable law.

Join phData, a remote-first data and AI consultancy company with employees across the United States, Latin America, and India. We partner with industry leaders, including Snowflake, AWS, Anthropic, Azure, GCP, Fivetran, Pinecone, Glean, and dbt, to solve the complex data and AI challenges that slow large enterprises.

We’re growing fast, and we give our people real ownership over their work. We hire top performers and trust them to deliver results.

Why phData?

• Snowflake Implementation Partner of the Year — 7 consecutive years, and 2026 Snowflake AI Partner of the Year
• AWS Premier Tier Services Partner — the highest tier of recognition in the AWS Partner Network
• 2025 Fivetran Partner of the Year (4th consecutive year)
• 2025 dbt Labs Partner of the Year (3x winner) with Visionary partner status
• 2026 KNIME Customer Excellence Partner of the Year
• Preferred Partner in the Anthropic Claude Partner Network
• #1 Partner in Snowflake Advanced Certifications
• 600+ Expert Cloud Certifications (Sigma, AWS, Azure, Dataiku, and more)
• Recognized as an award-winning workplace in the US, India and LATAM

We are looking for a Principal Solutions Architect to join our Machine Learning team. In this role, you will lead the architecture, implementation, and lifecycle management of AI/ML applications that deliver measurable business value for our clients. You will take full ownership of strategic AI/ML projects from vision and solution design through deployment and ongoing optimization, ensuring that models can be trained, tuned, and operated reliably using client data. You will collaborate closely with clients, Sales, data scientists, ML engineers, data engineers, platform/DevOps teams, and business stakeholders to deliver high-quality solutions and advance phData’s delivery excellence.

Key Responsibilities

• Own and drive end-to-end solution design and delivery of AI/ML and data solutions for strategic client accounts, ensuring reliable model deployment, retraining, monitoring, and production operations that create clear business impact.

• Translate complex business and data science requirements into scalable, secure, and resilient AI/ML architectures, defining the environments, data flows, and infrastructure required for model development, training, tuning, and serving.

• Lead technical and strategic client engagements, including workshops, discovery sessions, and architecture reviews, to align stakeholders on AI/ML roadmaps, deployment approaches, and production-readiness standards.

• Ensure the quality, reliability, and observability of AI/ML solutions through robust testing strategies, documentation, monitoring, and governance that meet security, compliance, and performance expectations.

• Contribute to and leverage reusable assets such as reference architectures, accelerators, templates, and playbooks, while mentoring team members and partnering with Sales and account leadership to grow strategic AI/ML engagements.

About You

You are a customer-obsessed technical leader and consultant who enjoys solving complex data and AI/ML challenges while building trusted relationships with clients. You are equally comfortable discussing architecture with executives and diving deep into code, infrastructure, and data pipelines with engineering teams. You thrive in an outcomes-driven environment, manage multiple work streams with ease, and bring a blend of strong engineering skills, strategic thinking, and excellent communication to every engagement. You are comfortable operating in distributed, global teams and partnering with colleagues across time zones.

Required Qualifications

Experience

• 10+ years of experience as a Machine Learning Engineer, Software Engineer, Data Engineer, or Data Scientist building and deploying production data and machine learning solutions.

Technical / Functional Skills

• Strong proficiency in a modern programming language such as Python (or similar) for building production-grade data and ML solutions, including experience designing and integrating APIs and services that expose ML models.

• Ability to build and operate robust data pipelines across diverse data sources and toolsets, with strong working knowledge of SQL and experience writing, debugging, and optimizing complex and distributed queries.

• Hands-on experience with big data and analytics platforms such as Spark, Snowflake, Databricks, Redshift, Amazon EMR, HDFS, or similar large-scale data processing and storage technologies.

• Familiarity with multiple data source systems such as JMS, Kafka, RDBMS, data warehouses, MySQL, Oracle, and SAP, and how they integrate into analytical and ML environments.

• Systems-level knowledge of network and cloud architecture, Linux-based operating systems, and storage/compute platforms (e.g., AWS, Databricks, Cloudera), with proven experience designing and operating production ML systems for performance, security, scalability, and reliability.

• End-to-end software development lifecycle experience (design, documentation, implementation, testing, deployment, and ongoing operations) for data and ML solutions, including model deployment, monitoring, and lifecycle management.

Education - If desired

• Bachelor’s degree in a relevant technical field (such as Computer Science) or equivalent practical experience.

Preferred Qualifications

Preferred qualifications help candidates stand out but are not required for success in this role.

• Experience with cloud and data ecosystem technologies such as Spark, Databricks, Snowflake, AWS, Azure, or GCP in the context of building and operating AI/ML solutions.

• Experience working with data science and machine learning libraries and frameworks such as H2O, TensorFlow, Keras, scikit-learn, or similar.

• Experience with containerization and orchestration technologies such as Docker and Kubernetes, and with MLOps tooling such as AWS SageMaker, Azure ML, and MLflow for enterprise-scale ML.

• Background in consulting or professional services, including pre-sales, project scoping, and strategic advisory work for data and AI/ML initiatives.

• Contributions to technical communities, open source projects, public speaking, writing, or other relevant side projects demonstrating thought leadership in data and AI/ML.

Why phData?

• Impactful Work: Partner with leading organizations on meaningful data & AI initiatives.
• Collaborative Culture: Work with a supportive, high-performing global team that values transparency, autonomy, and continuous improvement.
• Growth Opportunities: Access to challenging projects, mentorship, and structured development pathways.
• Values-Driven: We prioritize doing the right thing for our clients, our teams, and our community.

Benefits at phData

US:

• Remote-First Work Environment
• 401k plan with company match
• Dental and Vision insurance
• Home Office Equipment Stipend
• Annual stipend for Learning and Development
• Competitive comp, excellent benefits, 4 weeks PTO plan plus 10 Holidays (and other cool perks)

phData celebrates diversity and is committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at phData. We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at People Operations.

About TRG

TRG is on a mission to make the world a safer place. We build AI and data fusion solutions that help government agencies and national security organisations connect intelligence from across domains - cyber, physical, financial, and location - and turn it into decisions that protect people. The work is meaningful, the problems are hard, and the impact is real.

About the Role

We’re looking for a Data & AI Technical Lead to work closely with our Principal Data Engineer - taking ownership of technical design and architecture across data and AI systems, and acting as a reliable force multiplier for the team. This is a hands-on role - you design and you build.

The scope spans the full data and AI layer: how data flows between systems, how it is shaped for AI consumption, how agents and services are architected to work together reliably at scale. You’ll work in close partnership with the Principal Data Engineer, jointly shaping the architecture and evolution of the Data & AI domain. You’ll be expected to independently make and own technical decisions, drive initiatives from design through production, and provide technical leadership across the team.

You’ll work across teams and contribute to shaping how we approach Data Fusion: bringing together signals from heterogeneous systems and turning them into actionable insights through AI and data engineering. This requires someone who can hold the big picture in their head while still caring deeply about the details of implementation.

Beyond architecture, you’ll own the technical execution of initiatives within the Data & AI domain - driving work from design through production, making trade-off decisions, coordinating with adjacent teams, and staying accountable for systems after they go live.

We write code with AI - tools like Claude Code and Cursor are a core part of how we work at every level, including this one. At Technical Lead level we expect not just fluency but deliberate, opinionated use: knowing when to lean on AI, when to steer it hard, and when to step in entirely. This is a non-negotiable part of how we operate.

What You’ll Do

• Co-own technical architecture and system design with the Principal Data Engineer - covering data pipelines, AI flows, agent systems, and service integration patterns
• Lead design of data and AI flows across heterogeneous systems - defining how data is ingested, transformed, stored, retrieved, and consumed by agents and services
• Make and document architectural decisions independently when needed, providing clear reasoning and trade-off analysis
• Design and build MCP tools, RAG pipelines, and agent-facing APIs that connect AI systems to the data layer reliably
• Develop backend services with FastAPI as part of an event-driven architecture - hands-on, not just advisory
• Set and uphold engineering standards across the team: code quality, design patterns, review culture, and documentation practices
• Mentor engineers across the team - particularly on system design, data modelling, and AI integration patterns
• Use AI-assisted coding tools deliberately and help shape how the team uses them effectively
• Own the evolution of the Data & AI domain architecture, identifying technical debt, improving system design, and ensuring the long-term scalability and reliability of the platform
• Lead technical execution of initiatives from discovery to production - defining technical plans, driving implementation, overseeing rollout, and remaining accountable for post-release outcomes
• Act as the technical point of contact for initiatives within the domain, coordinating with Product Managers, engineers, QA, and adjacent teams to ensure successful delivery
• Collaborate closely with other Technical Leads and Principal Engineers to define shared interfaces, integration patterns, and cross-domain architectural decisions
• Drive engineering excellence in production through observability, monitoring, testing strategies, and operational readiness
• Participate in technical hiring and help shape the growth and technical direction of the Data & AI team

What We’re Looking For

• Strong Python engineering background - production-grade code across data pipelines, backend services, and AI integrations; you write things that last and that others can extend
• Data architecture experience - proven ability to design systems that handle data at scale: schema design, storage strategy, pipeline architecture, and data modelling for both analytical and AI workloads
• AI systems design - solid understanding of how LLMs, agents, and retrieval systems fit together; experience designing or building RAG pipelines, multi-agent systems, or tool-augmented LLM workflows
• Backend and API development - strong experience with FastAPI or equivalent; comfortable designing service contracts and integration patterns across systems
• Event-driven architecture - hands-on experience designing and operating event-driven systems in production (Kafka, RabbitMQ, or similar)
• Docker and containerisation - confident at developer and service level; able to reason about runtime environments and integration
• Technical leadership without authority - you influence through technical credibility, clear communication, and good judgment; you can drive alignment across engineers with different perspectives
• AI-first development - you code with AI tools as a genuine daily collaborator; at this level we expect you to have a formed point of view on how to use them well, not just a willingness to try
• Ownership mindset - you see a problem and you own it through to resolution; you don’t wait for someone to hand you a scope
• Adaptability - comfortable in exploratory, fast-moving environments where the right answer isn’t always obvious and requirements evolve
• Delivery ownership - experience leading technical initiatives end-to-end, from requirements and architecture through implementation, rollout, and production support; comfortable owning outcomes, not just implementation
• Cross-functional collaboration - ability to partner effectively with Product Managers, QA, and engineers across domains, balancing technical quality with delivery needs and business priorities
• Systems ownership mindset - experience operating production systems, with a strong focus on observability, reliability, incident response, and continuous improvement after release

Nice to have:

AI & Agents

• Experience with agent frameworks (LangChain, LangGraph, CrewAI, AutoGen, or similar)
• Familiarity with MCP (Model Context Protocol) and tool-use patterns in LLM systems
• Experience with vector databases or embedding-based retrieval
• Prompt engineering at scale - versioning, evaluation, and systematic iteration
• Deeper knowledge of LLMs, Neural Networks, concept of Fine Tuning, etc.

Data Engineering

• Experience with columnar or analytical databases (ClickHouse or similar)
• Familiarity with orchestration tools (Airflow, Prefect, Dagster, or similar)
• Background working across heterogeneous data sources and integration patterns

Your perks

• Working from home Hit your goals from the comfort of your home because we value the performance, not the place.
• Flexible hours because we promote work-life balance.
• Yearly performance bonus to reward good performance and hard work.
• Paid medical insurance because we like to take care of you.
• Daily lunch allowance so you can save lots of money, time, and effort by enjoying your free lunch at the office or home every day.
• Sport/Gym(Exercise) allowance to focus more on yourself, your well-being, and your health.
• Udemy unlimited subscription to promote your learning and development and grow your career.
• Onboarding plan and training so that you have a smooth induction and feel confident and ready to take over your new role.
• Equipment support so you have all the tools to do effectively and efficiently your work.
• No dress code because we want you to be as comfortable as possible.
• Gifts and rewards for celebrating birthdays, anniversaries, and personal milestones.
• Happy hours, coffee time, online team building, company events, and much more to promote team bonding and of course to have fun!
• Fresh fruit, snacks, coffee, and tea at the office because work makes us hungry!

About us

TRG TECH RESEARCH GROUP LIMITED deals with Data Fusion and AI products for civilian protection.

Our mission is to empower our customers to fight crime and terror through state-of-the-art technologies that provide accurate and precise intelligence.

Our product, Intellectus, is the only cloud-based all-in-one fusion platform with integrated web intelligence, discovery capabilities, advertisement intelligence, virtual ID management, and third-party database integration that can be deployed in less than 24 hours.

Want to learn more? Visit our website at www.trgint.com and our LinkedIn page.

TRG TECH RESEARCH GROUP LIMITED processes and/or controls all data in accordance with the EU General Data Protection Regulation (GDPR) 2016⁄679. For more information, visit our Privacy Policy.

Join phData, a remote-first data and AI consultancy company with employees across the United States, Latin America, and India. We partner with industry leaders, including Snowflake, AWS, Anthropic, Azure, GCP, Fivetran, Pinecone, Glean, and dbt, to solve the complex data and AI challenges that slow large enterprises.

We’re growing fast, and we give our people real ownership over their work. We hire top performers and trust them to deliver results.

Why phData?

• Snowflake Implementation Partner of the Year — 7 consecutive years, and 2026 Snowflake AI Partner of the Year
• AWS Premier Tier Services Partner — the highest tier of recognition in the AWS Partner Network
• 2025 Fivetran Partner of the Year (4th consecutive year)
• 2025 dbt Labs Partner of the Year (3x winner) with Visionary partner status
• 2026 KNIME Customer Excellence Partner of the Year
• Preferred Partner in the Anthropic Claude Partner Network
• #1 Partner in Snowflake Advanced Certifications
• 600+ Expert Cloud Certifications (Sigma, AWS, Azure, Dataiku, and more)
• Recognized as an award-winning workplace in the US, India and LATAM

We are looking for a Principal Solutions Architect to join our Machine Learning team. In this role, you will lead the architecture, implementation, and lifecycle management of AI/ML applications that deliver measurable business value for our clients. You will take full ownership of strategic AI/ML projects from vision and solution design through deployment and ongoing optimization, ensuring that models can be trained, tuned, and operated reliably using client data. You will collaborate closely with clients, Sales, data scientists, ML engineers, data engineers, platform/DevOps teams, and business stakeholders to deliver high-quality solutions and advance phData’s delivery excellence.

Key Responsibilities

• Own and drive end-to-end solution design and delivery of AI/ML and data solutions for strategic client accounts, ensuring reliable model deployment, retraining, monitoring, and production operations that create clear business impact.

• Translate complex business and data science requirements into scalable, secure, and resilient AI/ML architectures, defining the environments, data flows, and infrastructure required for model development, training, tuning, and serving.

• Lead technical and strategic client engagements, including workshops, discovery sessions, and architecture reviews, to align stakeholders on AI/ML roadmaps, deployment approaches, and production-readiness standards.

• Ensure the quality, reliability, and observability of AI/ML solutions through robust testing strategies, documentation, monitoring, and governance that meet security, compliance, and performance expectations.

• Contribute to and leverage reusable assets such as reference architectures, accelerators, templates, and playbooks, while mentoring team members and partnering with Sales and account leadership to grow strategic AI/ML engagements.

About You

You are a customer-obsessed technical leader and consultant who enjoys solving complex data and AI/ML challenges while building trusted relationships with clients. You are equally comfortable discussing architecture with executives and diving deep into code, infrastructure, and data pipelines with engineering teams. You thrive in an outcomes-driven environment, manage multiple work streams with ease, and bring a blend of strong engineering skills, strategic thinking, and excellent communication to every engagement. You are comfortable operating in distributed, global teams and partnering with colleagues across time zones.

Required Qualifications

Experience

• 10+ years of experience as a Machine Learning Engineer, Software Engineer, Data Engineer, or Data Scientist building and deploying production data and machine learning solutions.

Technical / Functional Skills

• Strong proficiency in a modern programming language such as Python (or similar) for building production-grade data and ML solutions, including experience designing and integrating APIs and services that expose ML models.

• Ability to build and operate robust data pipelines across diverse data sources and toolsets, with strong working knowledge of SQL and experience writing, debugging, and optimizing complex and distributed queries.

• Hands-on experience with big data and analytics platforms such as Spark, Snowflake, Databricks, Redshift, Amazon EMR, HDFS, or similar large-scale data processing and storage technologies.

• Familiarity with multiple data source systems such as JMS, Kafka, RDBMS, data warehouses, MySQL, Oracle, and SAP, and how they integrate into analytical and ML environments.

• Systems-level knowledge of network and cloud architecture, Linux-based operating systems, and storage/compute platforms (e.g., AWS, Databricks, Cloudera), with proven experience designing and operating production ML systems for performance, security, scalability, and reliability.

• End-to-end software development lifecycle experience (design, documentation, implementation, testing, deployment, and ongoing operations) for data and ML solutions, including model deployment, monitoring, and lifecycle management.

Education - If desired

• Bachelor’s degree in a relevant technical field (such as Computer Science) or equivalent practical experience.

Preferred Qualifications

Preferred qualifications help candidates stand out but are not required for success in this role.

• Experience with cloud and data ecosystem technologies such as Spark, Databricks, Snowflake, AWS, Azure, or GCP in the context of building and operating AI/ML solutions.

• Experience working with data science and machine learning libraries and frameworks such as H2O, TensorFlow, Keras, scikit-learn, or similar.

• Experience with containerization and orchestration technologies such as Docker and Kubernetes, and with MLOps tooling such as AWS SageMaker, Azure ML, and MLflow for enterprise-scale ML.

• Background in consulting or professional services, including pre-sales, project scoping, and strategic advisory work for data and AI/ML initiatives.

• Contributions to technical communities, open source projects, public speaking, writing, or other relevant side projects demonstrating thought leadership in data and AI/ML.

Why phData?

• Impactful Work: Partner with leading organizations on meaningful data & AI initiatives.
• Collaborative Culture: Work with a supportive, high-performing global team that values transparency, autonomy, and continuous improvement.
• Growth Opportunities: Access to challenging projects, mentorship, and structured development pathways.
• Values-Driven: We prioritize doing the right thing for our clients, our teams, and our community.

Benefits at phData

US:

• Remote-First Work Environment
• 401k plan with company match
• Dental and Vision insurance
• Home Office Equipment Stipend
• Annual stipend for Learning and Development
• Competitive comp, excellent benefits, 4 weeks PTO plan plus 10 Holidays (and other cool perks)

phData celebrates diversity and is committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at phData. We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at People Operations.

Magical is building an agentic AI platform that brings “AI employees” into the workplace to execute repetitive, operationally critical work.

Our agents help organizations move faster, reduce manual work, and improve outcomes in areas where reliability matters—particularly healthcare. We work directly with customers to understand complex workflows, deploy AI agents into real operating environments, and turn what we learn into a more powerful and scalable platform.

The shift toward agentic work is already underway, and we are building the infrastructure and deployment playbook that will define how it happens.

Magical is backed by Greylock, Coatue, Altman Capital, Lightspeed, and other investors behind companies including OpenAI, Anthropic, Hugging Face, and Notion.

About the role

We are looking for a Tech Lead to raise the technical bar across Magical’s Forward Deployed Engineering team and take on our most difficult customer and platform challenges.

This is a highly senior individual-contributor role. You will remain deeply hands-on while providing technical leadership across multiple customers, deployments, and FDE workstreams.

You will step into complex or ambiguous situations, quickly understand what is going wrong, and lead the work required to solve it. You will also coach less experienced FDEs, review technical approaches, and help the broader team develop stronger judgment and execution skills.

You will report to the Head of Deployments and work closely with Forward Deployed Engineers, Deployment Strategy, Product, and Engineering.

What you’ll do

• Take the lead on Magical’s most complex, high-risk, or technically ambiguous customer deployments.

• Get hands-on in the work—designing agentic workflows, writing and improving prompts, building integrations, debugging failures, analyzing system behavior, and shipping production solutions.

• Diagnose difficult issues across customer environments, integrations, agent performance, data quality, and platform behavior.

• Provide technical leadership across multiple customers and teams rather than owning only a single project or account.

• Review solution designs, implementation plans, testing strategies, and production-readiness for complex workflows.

• Coach FDEs through technical problems and help junior team members develop stronger problem-solving, debugging, and systems-thinking skills.

• Set an example for technical ownership, execution quality, urgency, and customer focus.

• Identify risks, architectural weaknesses, and reliability issues before they become customer-facing problems.

• Partner with Product and Engineering to distinguish between deployment-specific issues and platform-level gaps.

• Translate recurring customer challenges into reusable platform capabilities, internal tools, reference implementations, and technical standards.

• Improve the team’s practices for testing, observability, debugging, incident response, documentation, and release management.

• Help define what excellent Forward Deployed Engineering looks like at Magical.

What success looks like

• Magical’s technical deployments are delivered on time and thoroughly.

• Customer-facing issues are diagnosed accurately, with root causes addressed rather than repeatedly patched.

• FDEs make better technical decisions and become more capable of solving complex problems independently.

• Technical quality becomes more consistent across customers and workstreams.

• Repeated implementations are converted into reusable tools, patterns, and platform improvements.

• Product and Engineering receive clear, technically credible feedback from customer deployments.

• The organization can take on more complex customers without relying on a small number of people to repeatedly rescue deployments.

About you

• You have significant experience in software engineering, Forward Deployed Engineering, solutions engineering, systems integration, implementation engineering, or a similarly hands-on technical role.

• You have operated as a technical lead or senior individual contributor on complex, customer-facing software deployments.

• You are comfortable moving across the full problem space—from understanding a customer workflow to debugging an integration, improving agent behavior, and shipping a reliable production solution.

• You are an exceptional problem solver who can bring structure to unclear situations and make progress without complete information.

• You have strong technical judgment and know when to fix a local implementation, change the architecture, or escalate a platform limitation.

• You enjoy being hands-on and are willing to personally take on difficult implementation and debugging work.

• You are able to influence and lead other engineers without relying on formal management authority.

• You are a strong coach who can explain not only what should change, but how to think about the problem differently.

• You communicate clearly with engineers, deployment teams, and customer stakeholders, especially when a project is under pressure.

• You care deeply about production reliability, testing, observability, and solving the underlying cause of a problem.

• You are deeply curious about AI agents, prompting, automation, and multi-agent systems. Prior experience is valuable, but strong technical fundamentals and the ability to learn quickly matter more.

• You have a strong bias toward action and consistently demonstrate “show, don’t tell.”

• You have high agency and can prioritize, make decisions, and unblock yourself and others without waiting for perfect information.

• You are energized by early-stage environments where the technical playbook is still being created.

• You are located in Toronto or willing to relocate.

A science, engineering, or similarly technical educational background is helpful, but we care more about what you have built, solved, and learned than where you studied.

The reality of the role

This is not an advisory or architecture-only position. You will be expected to get into the details, work directly in the implementation, and stay close to a problem until it is solved.

You may move between customers, technical domains, and urgent priorities quickly. Some periods will involve intense work, incomplete information, and problems that do not have an obvious owner or solution.

You should be excited by the opportunity to step into those situations, create clarity, and lead from the front.

What we offer

• The opportunity to define the technical standard for Forward Deployed Engineering at Magical

• Ownership of some of the company’s most important and technically difficult customer problems

• A chance to work at the frontier of agentic AI and multi-agent systems

• Significant influence over Magical’s product, platform, and deployment practices

• A modern technical stack and access to leading AI tools

• Competitive compensation and meaningful equity

• Unlimited PTO

• Team offsites, with past trips including Iceland, Lisbon, Cancún, and Costa Rica

Magical is building an agentic AI platform that brings “AI employees” into the workplace to execute repetitive, operationally critical work.

Our agents help organizations move faster, reduce manual work, and improve outcomes in areas where reliability matters—particularly healthcare. We work directly with customers to understand complex workflows, deploy AI agents into real operating environments, and turn what we learn into a more powerful and scalable platform.

The shift toward agentic work is already underway, and we are building the infrastructure and deployment playbook that will define how it happens.

Magical is backed by Greylock, Coatue, Altman Capital, Lightspeed, and other investors behind companies including OpenAI, Anthropic, Hugging Face, and Notion.

About the role

We are looking for a Tech Lead to raise the technical bar across Magical’s Forward Deployed Engineering team and take on our most difficult customer and platform challenges.

This is a highly senior individual-contributor role. You will remain deeply hands-on while providing technical leadership across multiple customers, deployments, and FDE workstreams.

You will step into complex or ambiguous situations, quickly understand what is going wrong, and lead the work required to solve it. You will also coach less experienced FDEs, review technical approaches, and help the broader team develop stronger judgment and execution skills.

You will report to the Head of Deployments and work closely with Forward Deployed Engineers, Deployment Strategy, Product, and Engineering.

What you’ll do

• Take the lead on Magical’s most complex, high-risk, or technically ambiguous customer deployments.

• Get hands-on in the work—designing agentic workflows, writing and improving prompts, building integrations, debugging failures, analyzing system behavior, and shipping production solutions.

• Diagnose difficult issues across customer environments, integrations, agent performance, data quality, and platform behavior.

• Provide technical leadership across multiple customers and teams rather than owning only a single project or account.

• Review solution designs, implementation plans, testing strategies, and production-readiness for complex workflows.

• Coach FDEs through technical problems and help junior team members develop stronger problem-solving, debugging, and systems-thinking skills.

• Set an example for technical ownership, execution quality, urgency, and customer focus.

• Identify risks, architectural weaknesses, and reliability issues before they become customer-facing problems.

• Partner with Product and Engineering to distinguish between deployment-specific issues and platform-level gaps.

• Translate recurring customer challenges into reusable platform capabilities, internal tools, reference implementations, and technical standards.

• Improve the team’s practices for testing, observability, debugging, incident response, documentation, and release management.

• Help define what excellent Forward Deployed Engineering looks like at Magical.

What success looks like

• Magical’s technical deployments are delivered on time and thoroughly.

• Customer-facing issues are diagnosed accurately, with root causes addressed rather than repeatedly patched.

• FDEs make better technical decisions and become more capable of solving complex problems independently.

• Technical quality becomes more consistent across customers and workstreams.

• Repeated implementations are converted into reusable tools, patterns, and platform improvements.

• Product and Engineering receive clear, technically credible feedback from customer deployments.

• The organization can take on more complex customers without relying on a small number of people to repeatedly rescue deployments.

About you

• You have significant experience in software engineering, Forward Deployed Engineering, solutions engineering, systems integration, implementation engineering, or a similarly hands-on technical role.

• You have operated as a technical lead or senior individual contributor on complex, customer-facing software deployments.

• You are comfortable moving across the full problem space—from understanding a customer workflow to debugging an integration, improving agent behavior, and shipping a reliable production solution.

• You are an exceptional problem solver who can bring structure to unclear situations and make progress without complete information.

• You have strong technical judgment and know when to fix a local implementation, change the architecture, or escalate a platform limitation.

• You enjoy being hands-on and are willing to personally take on difficult implementation and debugging work.

• You are able to influence and lead other engineers without relying on formal management authority.

• You are a strong coach who can explain not only what should change, but how to think about the problem differently.

• You communicate clearly with engineers, deployment teams, and customer stakeholders, especially when a project is under pressure.

• You care deeply about production reliability, testing, observability, and solving the underlying cause of a problem.

• You are deeply curious about AI agents, prompting, automation, and multi-agent systems. Prior experience is valuable, but strong technical fundamentals and the ability to learn quickly matter more.

• You have a strong bias toward action and consistently demonstrate “show, don’t tell.”

• You have high agency and can prioritize, make decisions, and unblock yourself and others without waiting for perfect information.

• You are energized by early-stage environments where the technical playbook is still being created.

• You are located in Toronto or willing to relocate.

A science, engineering, or similarly technical educational background is helpful, but we care more about what you have built, solved, and learned than where you studied.

The reality of the role

This is not an advisory or architecture-only position. You will be expected to get into the details, work directly in the implementation, and stay close to a problem until it is solved.

You may move between customers, technical domains, and urgent priorities quickly. Some periods will involve intense work, incomplete information, and problems that do not have an obvious owner or solution.

You should be excited by the opportunity to step into those situations, create clarity, and lead from the front.

What we offer

• The opportunity to define the technical standard for Forward Deployed Engineering at Magical

• Ownership of some of the company’s most important and technically difficult customer problems

• A chance to work at the frontier of agentic AI and multi-agent systems

• Significant influence over Magical’s product, platform, and deployment practices

• A modern technical stack and access to leading AI tools

• Competitive compensation and meaningful equity

• Unlimited PTO

• Team offsites, with past trips including Iceland, Lisbon, Cancún, and Costa Rica

Magical is building an agentic AI platform that brings “AI employees” into the workplace to execute repetitive, operationally critical work.

Our agents help organizations move faster, reduce manual work, and improve outcomes in areas where reliability matters—particularly healthcare. We work directly with customers to understand complex workflows, deploy AI agents into real operating environments, and turn what we learn into a more powerful and scalable platform.

The shift toward agentic work is already underway, and we are building the infrastructure and deployment playbook that will define how it happens.

Magical is backed by Greylock, Coatue, Altman Capital, Lightspeed, and other investors behind companies including OpenAI, Anthropic, Hugging Face, and Notion.

About the role

We are looking for a Tech Lead to raise the technical bar across Magical’s Forward Deployed Engineering team and take on our most difficult customer and platform challenges.

This is a highly senior individual-contributor role. You will remain deeply hands-on while providing technical leadership across multiple customers, deployments, and FDE workstreams.

You will step into complex or ambiguous situations, quickly understand what is going wrong, and lead the work required to solve it. You will also coach less experienced FDEs, review technical approaches, and help the broader team develop stronger judgment and execution skills.

You will report to the Head of Deployments and work closely with Forward Deployed Engineers, Deployment Strategy, Product, and Engineering.

What you’ll do

• Take the lead on Magical’s most complex, high-risk, or technically ambiguous customer deployments.

• Get hands-on in the work—designing agentic workflows, writing and improving prompts, building integrations, debugging failures, analyzing system behavior, and shipping production solutions.

• Diagnose difficult issues across customer environments, integrations, agent performance, data quality, and platform behavior.

• Provide technical leadership across multiple customers and teams rather than owning only a single project or account.

• Review solution designs, implementation plans, testing strategies, and production-readiness for complex workflows.

• Coach FDEs through technical problems and help junior team members develop stronger problem-solving, debugging, and systems-thinking skills.

• Set an example for technical ownership, execution quality, urgency, and customer focus.

• Identify risks, architectural weaknesses, and reliability issues before they become customer-facing problems.

• Partner with Product and Engineering to distinguish between deployment-specific issues and platform-level gaps.

• Translate recurring customer challenges into reusable platform capabilities, internal tools, reference implementations, and technical standards.

• Improve the team’s practices for testing, observability, debugging, incident response, documentation, and release management.

• Help define what excellent Forward Deployed Engineering looks like at Magical.

What success looks like

• Magical’s technical deployments are delivered on time and thoroughly.

• Customer-facing issues are diagnosed accurately, with root causes addressed rather than repeatedly patched.

• FDEs make better technical decisions and become more capable of solving complex problems independently.

• Technical quality becomes more consistent across customers and workstreams.

• Repeated implementations are converted into reusable tools, patterns, and platform improvements.

• Product and Engineering receive clear, technically credible feedback from customer deployments.

• The organization can take on more complex customers without relying on a small number of people to repeatedly rescue deployments.

About you

• You have significant experience in software engineering, Forward Deployed Engineering, solutions engineering, systems integration, implementation engineering, or a similarly hands-on technical role.

• You have operated as a technical lead or senior individual contributor on complex, customer-facing software deployments.

• You are comfortable moving across the full problem space—from understanding a customer workflow to debugging an integration, improving agent behavior, and shipping a reliable production solution.

• You are an exceptional problem solver who can bring structure to unclear situations and make progress without complete information.

• You have strong technical judgment and know when to fix a local implementation, change the architecture, or escalate a platform limitation.

• You enjoy being hands-on and are willing to personally take on difficult implementation and debugging work.

• You are able to influence and lead other engineers without relying on formal management authority.

• You are a strong coach who can explain not only what should change, but how to think about the problem differently.

• You communicate clearly with engineers, deployment teams, and customer stakeholders, especially when a project is under pressure.

• You care deeply about production reliability, testing, observability, and solving the underlying cause of a problem.

• You are deeply curious about AI agents, prompting, automation, and multi-agent systems. Prior experience is valuable, but strong technical fundamentals and the ability to learn quickly matter more.

• You have a strong bias toward action and consistently demonstrate “show, don’t tell.”

• You have high agency and can prioritize, make decisions, and unblock yourself and others without waiting for perfect information.

• You are energized by early-stage environments where the technical playbook is still being created.

• You are located in Toronto or willing to relocate.

A science, engineering, or similarly technical educational background is helpful, but we care more about what you have built, solved, and learned than where you studied.

The reality of the role

This is not an advisory or architecture-only position. You will be expected to get into the details, work directly in the implementation, and stay close to a problem until it is solved.

You may move between customers, technical domains, and urgent priorities quickly. Some periods will involve intense work, incomplete information, and problems that do not have an obvious owner or solution.

You should be excited by the opportunity to step into those situations, create clarity, and lead from the front.

What we offer

• The opportunity to define the technical standard for Forward Deployed Engineering at Magical

• Ownership of some of the company’s most important and technically difficult customer problems

• A chance to work at the frontier of agentic AI and multi-agent systems

• Significant influence over Magical’s product, platform, and deployment practices

• A modern technical stack and access to leading AI tools

• Competitive compensation and meaningful equity

• Unlimited PTO

• Team offsites, with past trips including Iceland, Lisbon, Cancún, and Costa Rica

Headquarters: United States - Remote

We're transforming the grocery industry

At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.

Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.

Instacart is a Flex First team

There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.

 

Overview

The Commercial Scaled Intelligence (CSI) team is an AI-first team dedicated to delivering actionable commercial insights and scalable automation to drive revenue growth and operational efficiency across the company. The team focuses on intelligence generation, predictive analytics, and workflow automation to enable data-driven decision-making and optimize commercial performance.

As an Ads AI Analytics Lead II, you will own the intelligence behind our Ads agents. You will design the Ads semantic/context layer and build vertical AI agents that analyze campaigns, diagnose performance, and recommend actions that improve ROAS, pacing, and partner outcomes. You will partner with Ads GTM, Product, Data Science, and Engineering to ship production agents with measurable lift.

 

About the Job

• Define Ads ontologies and metrics for campaigns, budgets, bids, creatives, audiences, and placements.
• Build dbt models and curated marts in Snowflake with clear data contracts, tests, and SLOs.
• Ingest and enrich unstructured Ads content and publish retrieval‑ready datasets using our managed search/vector services.
• Design and evaluate retrieval workflows (RAG) with existing services for hybrid search and re‑ranking; set quality/latency targets and iterate via experiments.
• Design agent reasoning and policies on ads, including tool definitions and human‑in‑the‑loop approvals.
• Establish evaluation suites covering precision/recall, calibration, hallucination rate, latency, and cost.
• Run A/B or uplift experiments to quantify impact and guide iteration.
• Translate Ads problems into agent behaviors and own KPIs such as ROAS lift, pacing accuracy, RCA precision/recall, forecast MAPE, and time‑to‑insight.

 

About You

Minimum Qualifications

• 3–6 years in analytics engineering, data science, or applied AI with strong SQL and Python.
• 2+ years of domain expertise in ads, retail, or e-commerce data.
• Advanced Proficiency in Python and SQL, with experience using dbt and Snowflake or BigQuery, including skills in data modeling, testing, and managing data contracts.
• Deep Expertise in orchestrating data pipelines using dbt and Airflow
• Experience with at least one data visualization tool (Tableau, Mode, Power BI, Looker, or similar)
• Ability to design offline/online evaluations and run A/B or uplift tests
• Fluency in Ads analytics concepts such as ROAS, CPA, CTR, CVR, LTV, pacing, auction dynamics, and incrementality.
• Strong stakeholder communication with a track record of shipping production data or AI systems that drove business impact.
• Understanding of ML models to drive recommendations on bid, keywords, and budgets
• Experience with evaluation and guardrail frameworks and human‑in‑the‑loop QA.

Preferred Qualifications

• Strong understanding of AI and machine learning concepts, with experience creating AI-driven products.
• Deep expertise in advertising products, including leading and driving automation projects.
• Proven ability to improve operational efficiency through automation initiatives in fast-paced environments.
• Applied experience in modeling techniques for Ads, including forecasting, anomaly detection, uplift modeling, and causal inference.
• Hands-on experience with workflow automation and low-code development platforms (Zapier, n8n, Gumloop, Superblocks)
• Familiarity with retail media or ad platforms, including Amazon, Google, Meta, Shopify, or DoorDash.

 

#LI-Remote

Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here.

Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here.

For US based candidates, the base pay ranges for a successful candidate are listed below.

CA, NY, CT, NJ$157,000—$165,000 USDWA$150,000—$159,000 USDOR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI$144,000—$152,000 USDAll other states$131,000—$138,000 USD

To apply: https://weworkremotely.com/remote-jobs/instacart-ads-ai-analytics-lead-ii

Headquarters: Tallinn, Remote, Estonia
URL: http://capslock.global

CapsLock is a global IT marketing company that pioneers unique, scalable customer acquisition solutions for B2C clients. We solve complex sales challenges across a wide range of industries, primarily for large North American partners. By integrating our expertise in Digital Marketing, IT, Design, AI-driven analytics, proprietary MarTech, and sales consulting, we deliver powerful, data-informed customer acquisition solutions.

At CapsLock, people, technology, and forward-thinking innovation lie at the heart of everything we do. Our diverse, global team, fluent in over 10 languages, thrives on open collaboration and the exchange of new ideas, pushing boundaries to ensure our clients' success.

Role overview

We are building CapsLock's AI Media Production platform, and we're hiring the tech lead who will architect it.

We generate visuals of real products, not concepts. Every asset must match the client's actual product 1:1 - down to hardware and geometry. No artifacts, no hallucinations, no "close enough". This is a control and reproducibility problem, not a prompting problem, and it needs an engineer.

This is a greenfield build. You'll be the first engineer in this direction, working directly with the Design Director as the technical interface between creative teams and software infrastructure.

What you will work on

• Architect and run our AI Media Production platform: serving ComfyUI or similar engines, GPU environments, one-click UIs for non-technical teams;
• Ship modular, versioned, reproducible generative pipelines, node-based and/or code-first (e.g. diffusers);
• Develop one-click presets and use cases for image and video generation;
• Train LoRAs end-to-end: from real product photography to evaluated, production-ready models;
• Build control-first generation into every pipeline: ControlNet, IP-Adapter, inpainting, reference conditioning;
• Engineer QC into the pipeline itself: automated checks against product references, before a human ever reviews;
• Build our creative intelligence loop: encode what makes our best-performing assets work into reusable presets and styles;
• Own the technical roadmap with the Design Director; qualify new models and tools; drive adoption through enablement, not mandates.

Your must haves

You don't need to meet every single requirement. If you're excellent in most of these areas and can show shipped work, we'd love to hear from you.

• Shipped generative pipelines adopted and used daily by other people;
• Production-grade workflows in ComfyUI or similar technologies, or equivalent code-first experience (e.g. diffusers);
• Strong Python: automation, API integrations, custom nodes;
• LoRA training end-to-end, from dataset curation to evaluation;
• Control techniques across modalities (t2i, i2i, i2v, v2v): ControlNet, IP-Adapter, inpainting, reference conditioning;
• Deploying pipelines as internal tools;
• Enough visual literacy to set the quality bar (no design portfolio required);
• Confident English (B2+).

Nice to have

• 3D/render-hybrid workflows: Blender or CAD renders as geometric ground truth with generated environments;
• LLM orchestration and agentic workflows: automated prompt generation, VLM-based QC;
• Experience producing visuals for performance marketing.

What we offer

• Remote Work - we offer a truly and fully remote environment. You choose where you are the most productive and comfortable to have an impact.
• Paid vacations - generous paid vacation policy to ensure you have time to recharge
• Unlimited Sick Days - we understand that being only human means getting sick or feeling under the weather from time to time, so we guarantee you time off as long as you need to recover and get back on your feet.
• Ongoing Learning - people at CapsLock are deeply inquisitive and eager to learn new knowledge and skills, that's why we support and create learning opportunities like the Free Books program, workshops, conferences, and more.
• Home Office - we will cover the equipment and furniture expenses to make sure you have the best work-from-home experience.
• Physical Well–Being - We will cover costs of your medical insurance. Additionally we offer an allowance for a flexible fitness program.
• Fun Stuff - there is never a shortage of fun stuff

To apply: https://weworkremotely.com/remote-jobs/capslock-generative-ai-pipeline-engineer-tech-lead-2

Headquarters: Tirana, Remote, Albania
URL: http://capslock.global

CapsLock is a global IT marketing company that pioneers unique, scalable customer acquisition solutions for B2C clients. We solve complex sales challenges across a wide range of industries, primarily for large North American partners. By integrating our expertise in Digital Marketing, IT, Design, AI-driven analytics, proprietary MarTech, and sales consulting, we deliver powerful, data-informed customer acquisition solutions.

At CapsLock, people, technology, and forward-thinking innovation lie at the heart of everything we do. Our diverse, global team, fluent in over 10 languages, thrives on open collaboration and the exchange of new ideas, pushing boundaries to ensure our clients' success.

Role overview

We are building CapsLock's AI Media Production platform, and we're hiring the tech lead who will architect it.

We generate visuals of real products, not concepts. Every asset must match the client's actual product 1:1 - down to hardware and geometry. No artifacts, no hallucinations, no "close enough". This is a control and reproducibility problem, not a prompting problem, and it needs an engineer.

This is a greenfield build. You'll be the first engineer in this direction, working directly with the Design Director as the technical interface between creative teams and software infrastructure.

What you will work on

• Architect and run our AI Media Production platform: serving ComfyUI or similar engines, GPU environments, one-click UIs for non-technical teams;
• Ship modular, versioned, reproducible generative pipelines, node-based and/or code-first (e.g. diffusers);
• Develop one-click presets and use cases for image and video generation;
• Train LoRAs end-to-end: from real product photography to evaluated, production-ready models;
• Build control-first generation into every pipeline: ControlNet, IP-Adapter, inpainting, reference conditioning;
• Engineer QC into the pipeline itself: automated checks against product references, before a human ever reviews;
• Build our creative intelligence loop: encode what makes our best-performing assets work into reusable presets and styles;
• Own the technical roadmap with the Design Director; qualify new models and tools; drive adoption through enablement, not mandates.

Your must haves

You don't need to meet every single requirement. If you're excellent in most of these areas and can show shipped work, we'd love to hear from you.

• Shipped generative pipelines adopted and used daily by other people;
• Production-grade workflows in ComfyUI or similar technologies, or equivalent code-first experience (e.g. diffusers);
• Strong Python: automation, API integrations, custom nodes;
• LoRA training end-to-end, from dataset curation to evaluation;
• Control techniques across modalities (t2i, i2i, i2v, v2v): ControlNet, IP-Adapter, inpainting, reference conditioning;
• Deploying pipelines as internal tools;
• Enough visual literacy to set the quality bar (no design portfolio required);
• Confident English (B2+).

Nice to have

• 3D/render-hybrid workflows: Blender or CAD renders as geometric ground truth with generated environments;
• LLM orchestration and agentic workflows: automated prompt generation, VLM-based QC;
• Experience producing visuals for performance marketing.

What we offer

• Remote Work - we offer a truly and fully remote environment. You choose where you are the most productive and comfortable to have an impact.
• Paid vacations - generous paid vacation policy to ensure you have time to recharge
• Unlimited Sick Days - we understand that being only human means getting sick or feeling under the weather from time to time, so we guarantee you time off as long as you need to recover and get back on your feet.
• Ongoing Learning - people at CapsLock are deeply inquisitive and eager to learn new knowledge and skills, that's why we support and create learning opportunities like the Free Books program, workshops, conferences, and more.
• Home Office - we will cover the equipment and furniture expenses to make sure you have the best work-from-home experience.
• Physical Well–Being - We will cover costs of your medical insurance. Additionally we offer an allowance for a flexible fitness program.
• Fun Stuff - there is never a shortage of fun stuff

To apply: https://weworkremotely.com/remote-jobs/capslock-generative-ai-pipeline-engineer-tech-lead

Headquarters: Helsinki, Remote, Finland
URL: http://capslock.global

CapsLock is a global IT marketing company that pioneers unique, scalable customer acquisition solutions for B2C clients. We solve complex sales challenges across a wide range of industries, primarily for large North American partners. By integrating our expertise in Digital Marketing, IT, Design, AI-driven analytics, proprietary MarTech, and sales consulting, we deliver powerful, data-informed customer acquisition solutions.

At CapsLock, people, technology, and forward-thinking innovation lie at the heart of everything we do. Our diverse, global team, fluent in over 10 languages, thrives on open collaboration and the exchange of new ideas, pushing boundaries to ensure our clients' success.

Role overview

We are building CapsLock's AI Media Production platform, and we're hiring the tech lead who will architect it.

We generate visuals of real products, not concepts. Every asset must match the client's actual product 1:1 - down to hardware and geometry. No artifacts, no hallucinations, no "close enough". This is a control and reproducibility problem, not a prompting problem, and it needs an engineer.

This is a greenfield build. You'll be the first engineer in this direction, working directly with the Design Director as the technical interface between creative teams and software infrastructure.

What you will work on

• Architect and run our AI Media Production platform: serving ComfyUI or similar engines, GPU environments, one-click UIs for non-technical teams;
• Ship modular, versioned, reproducible generative pipelines, node-based and/or code-first (e.g. diffusers);
• Develop one-click presets and use cases for image and video generation;
• Train LoRAs end-to-end: from real product photography to evaluated, production-ready models;
• Build control-first generation into every pipeline: ControlNet, IP-Adapter, inpainting, reference conditioning;
• Engineer QC into the pipeline itself: automated checks against product references, before a human ever reviews;
• Build our creative intelligence loop: encode what makes our best-performing assets work into reusable presets and styles;
• Own the technical roadmap with the Design Director; qualify new models and tools; drive adoption through enablement, not mandates.

Your must haves

You don't need to meet every single requirement. If you're excellent in most of these areas and can show shipped work, we'd love to hear from you.

• Shipped generative pipelines adopted and used daily by other people;
• Production-grade workflows in ComfyUI or similar technologies, or equivalent code-first experience (e.g. diffusers);
• Strong Python: automation, API integrations, custom nodes;
• LoRA training end-to-end, from dataset curation to evaluation;
• Control techniques across modalities (t2i, i2i, i2v, v2v): ControlNet, IP-Adapter, inpainting, reference conditioning;
• Deploying pipelines as internal tools;
• Enough visual literacy to set the quality bar (no design portfolio required);
• Confident English (B2+).

Nice to have

• 3D/render-hybrid workflows: Blender or CAD renders as geometric ground truth with generated environments;
• LLM orchestration and agentic workflows: automated prompt generation, VLM-based QC;
• Experience producing visuals for performance marketing.

What we offer

• Remote Work - we offer a truly and fully remote environment. You choose where you are the most productive and comfortable to have an impact.
• Paid vacations - generous paid vacation policy to ensure you have time to recharge
• Unlimited Sick Days - we understand that being only human means getting sick or feeling under the weather from time to time, so we guarantee you time off as long as you need to recover and get back on your feet.
• Ongoing Learning - people at CapsLock are deeply inquisitive and eager to learn new knowledge and skills, that's why we support and create learning opportunities like the Free Books program, workshops, conferences, and more.
• Home Office - we will cover the equipment and furniture expenses to make sure you have the best work-from-home experience.
• Physical Well–Being - We will cover costs of your medical insurance. Additionally we offer an allowance for a flexible fitness program.
• Fun Stuff - there is never a shortage of fun stuff

To apply: https://weworkremotely.com/remote-jobs/capslock-generative-ai-pipeline-engineer-tech-lead-1

Company Description

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.

Job Description

Overview

As the senior technical authority for the DevX platform, you will define how AI-native software delivery works across the organization. You will connect core developer platform capabilities—such as CI/CD, Backstage, cloud landing zones, and software supply chain security—with AI agents, orchestration, governance, and enterprise knowledge systems. You will influence teams across engineering, security, and business units by setting technical direction and building working examples that others can adopt.

This is a Remote position. You will report to the EVP of Developer Experience & AI Tooling

You will have opportunity to:

• Set the end-to-end architecture for agentic software delivery, the developer portal, and the governed AI marketplace.
• Build reference implementations for agent orchestration, AI governance, Knowledge Graph grounding, and agent-enabled golden paths.
• Establish the internal AI architecture that makes governed model access, policy enforcement, and usage control the default across all developer AI tooling and agents.
• Define platform standards for SDKs, connectors, MCP servers, plugins, agents, and marketplace contributions.
• Partner with Security Engineering on SLSA provenance, SBOMs, policy-as-code, and AI supply chain controls.
• Connect CI/CD, cloud landing zones, Backstage, and AI capabilities into one secure developer platform.
• Resolve technical decisions that span platform, AI, security, and business unit engineering teams.
• Represent the platform’s technical direction with senior leaders, engineering teams, and external industry audiences.

Qualifications

• 8+ years of technology experience
• 3+ years as a Senior Architect or equivalent technical leadership role
• Recent hands-on experience building both developer platforms and AI-native engineering systems.
• Experience designing and operating enterprise-scale internal developer platforms.
• Experience building CI/CD pipelines, golden paths, and cloud-native landing zones.
• Production experience with agent orchestration, agentic workflows, and SDLC agents.
• Experience with enterprise retrieval, grounding, Knowledge Graphs, and prompt and context engineering.
• Experience integrating AI tools through MCP servers, connectors, APIs, or similar frameworks.
• Experience implementing SLSA, SBOMs, policy-as-code, and secure software supply chain practices.

Additional Information

Benefits/Perks

• Great compensation package and bonus plan
• Core benefits including medical, dental, vision, and matching 401K
• Flexible work environment, ability to work remote, hybrid or in-office
• Flexible time off including volunteer time off, vacation, sick and 12-paid holidays
• Explore all our exciting benefits here: https://yourexperianbenefits.com/cand-index.html
• #LI-Remote

Our uniqueness is that we celebrate yours. Experian’s people first, inclusive and purpose driven culture is multi award-winning; World’s Best Workplaces™ 2025 (Fortune Global Top 25), Great Place To Work™ in 26 countries to name a few. Check out Experian Life on social or explore our Careers Site to understand why.

Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay range for this position is listed above. Within this range, individual pay is determined by work location and additional factors such as job-related skills, experience, and education. This position is also eligible for a variable pay opportunity and a comprehensive benefits package.

Recruitment Fraud Awareness - Experian’s recruitment process is conducted only through authorised channels. Recruitment communications will only be sent from an @experian.com email address. Experian will never ask candidates to make any payment as part of an application, interview, assessment, onboarding, or recruitment process. To apply for roles or verify opportunities, please visit experian.com/careers.

Experian is proud to be an Equal Opportunity Employer for all groups protected under applicable federal, state and local law, including protected veterans and individuals with disabilities. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

About Us:

Spreedly is the world’s leading Open Payments Platform. Founded in 2007 and headquartered in Durham, NC, the company gives mid-market and enterprise businesses the infrastructure to connect to any payment gateway, processor, or fraud tool through a single API. The platform is vendor-agnostic by design, meaning customers are never locked into a single provider and never need to rebuild their payments stack to access new capabilities.

The core business problem Spreedly solves is real and costly: global merchants face a fragmented payments ecosystem, where every new market, payment method, or fraud tool typically requires a separate, time-consuming integration. Spreedly eliminates that complexity, enabling companies to route transactions intelligently, secure cardholder data, prevent fraud, and expand into new markets without heavy engineering overhead.

Product Offering:

Spreedly provides an open payments platform. The platform’s connectivity provides payments performance. Key products and services include:

Connect— A unified API that integrates with hundreds of payment gateways, processors, and alternative payment methods worldwide, including digital wallets. Merchants access the global payments ecosystem through one connection.

Vault — A PCI-compliant secure repository for payment methods. Merchants store card data once and reuse it across any payment service, reducing PCI scope and protecting cardholder data at scale.

Optimize— Workflow-driven routing and retry logic that directs each transaction to the best-performing gateway in real time. On average, 7.9% of failed transactions succeed immediately when retried on a secondary gateway. This is where merchants recover lost revenue and increase authorization success rates.

Protect— A flexible fraud and authentication layer, incorporating advanced fraud tools and 3DS. Following Spreedly’s acquisition of Dodgeball in September 2025, fraud orchestration and payment optimization now operate within the same platform.

Resolve— Centralized management and reporting that reduces operational silos, strengthens security, and improves billing control across a merchant’s entire payment operation.

What It’s Like to Work Here:

We describe our team as “Spreedlings”: diverse, forward-thinking, and driven by a shared belief that a more open payments ecosystem benefits everyone. The company operates with a culture built on transparency, courageous collaboration, and self-driven leadership. The team values simplicity in both product and process, and approaches problem-solving with genuine curiosity.

About the Role:

We’re looking for a Business AI Operations Lead to help Spreedly transform how business teams operate by identifying high-value opportunities and translating them into practical, scalable AI-enabled workflows.

This role leads AI workflow discovery across R&D and builds prioritized solutions across R&D and other business functions. It also owns key Marketing Operations activities outside of scoring, routing, and analytics, which are managed by Revenue Operations.

The ideal candidate combines strong operational judgment with hands-on implementation skills. They can understand how work happens today, identify opportunities for meaningful improvement, and deliver practical solutions that teams adopt and continue to use.

Success in this role will be measured by the on-time delivery of prioritized workflows, improved operational efficiency, strong adoption, measurable business outcomes, and reliable processes and solutions.

Responsibilities:

R&D Workflow Discovery

• Lead AI workflow discovery across Product, Engineering, and other R&D functions.
• Partner with stakeholders to understand business needs, operational challenges, and existing processes.
• Identify opportunities where AI and automation can reduce manual work, improve execution, or increase productivity.
• Document and maintain identified R&D opportunities in the shared company AI workflow inventory for prioritization.
• Translate selected opportunities into clear requirements, success measures, and implementation plans.

Business AI Execution

• Design and build prioritized AI workflows across R&D and other business functions.
• Translate business requirements into practical solutions using approved AI platforms and shared capabilities.
• Deliver assigned solutions on time and communicate risks or delays early.
• Focus primarily on operational AI workflows that can deliver measurable business value.
• Test solutions with business users, incorporate feedback, and support successful adoption.
• Partner with the AI Enablement & Solutions Lead when initiatives require advanced architecture, reusable capabilities, or complex cross-functional design.
• Apply shared AI standards and recommended implementation patterns to assigned solutions.

Solution Ownership

• Serve as the AI build owner for assigned workflows.
• Own solution design, development, testing, launch, maintenance, and ongoing optimization.
• Partner with internal business customers to validate requirements, support adoption, and measure business outcomes.
• Develop documentation, user guidance, and training materials for delivered solutions.
• Monitor solution performance and identify opportunities for continued improvement.
• Ensure assigned workflows remain aligned with shared AI standards and company priorities.

Marketing Operations

• Own Marketing Operations activities outside of scoring, routing, and analytics.
• Manage campaign operations and configuration, nurture programs, audience segmentation, webinars, and marketing automation.
• Support data quality, source management, auditing, lead-flow execution, and operational governance in partnership with Revenue Operations.
• Optimize the marketing technology stack, including HubSpot, Salesforce, Influ2, and related platforms.
• Partner with Revenue Operations on processes and systems involving scoring, routing, analytics, and reporting.
• Ensure Marketing Operations processes and workflows remain scalable, reliable, and well maintained.

Requirements:

• 5+ years of experience in Business Operations, Marketing Operations, process improvement, automation, or a related field.
• Hands-on experience designing, implementing, and maintaining operational workflows.
• Experience using Claude or similar tools to build AI-enabled business workflows.
• Experience with APIs, low-code or no-code platforms, workflow automation, or prompt engineering.
• Experience applying AI or automation to improve business processes and productivity.
• Strong ability to translate business needs into practical, usable solutions.
• Experience with business systems, workflow automation, and modern technology platforms.
• Experience with HubSpot, Salesforce, or comparable business platforms.
• Demonstrated ability to drive adoption and organizational change without direct authority.
• Strong analytical, project-management, communication, and stakeholder-management skills.
• Ability to manage multiple priorities across different business functions.
• Strong attention to detail and commitment to reliable, maintainable execution.

Additional Skills We Value:

• Experience with n8n, Apollo, Clay, Influ2, or similar platforms.
• Experience supporting Product, Engineering, Marketing, Sales, Customer Success, or Revenue Operations.
• Experience with SQL, reporting, analytics, or data visualization.
• Experience in SaaS, fintech, payments, or another technology environment.
• Experience supporting AI workflow discovery or business process redesign.

We Offer Our US-Based Employees:

• Competitive salary + Equity
• Outstanding Medical and Dental benefits, including 100% employer-paid options
• Company-paid Life and Disability insurance
• Optional vision and supplemental insurance options, and various Flexible Spending Accounts (FSA)
• Open Paid Time Off policy + 12 weeks of paid leave for new parents
• Matching 401(k) plan (5% up to $5,000 yearly)
• $1,000 annual professional development stipend
• Monthly home working/digital lifestyle stipend, new MacBook, and one-time accessory reimbursement
• Access to company-paid professional coaching service
• Visits to HQ in Durham, North Carolina for remote employees

#LI-AE1

We champion the ethical, creative use of AI—if you’re someone who pairs human judgment with modern AI tools to work smarter and drive bigger impact, you’ll thrive here.

–

Spreedly is an equal opportunity employer. We are committed to fostering, cultivating, and preserving a culture of diversity, equity, inclusion, and belonging. We actively work to drive out even unintentional discrimination in our hiring processes via practices like blindly graded work samples, structured interviews, and diversity awareness training.

Due to the sensitive nature of what Spreedly does - handling payment data - finalist candidates must complete a successful background and reference check.

At this time Spreedly is unable to provide sponsorship for employment, and we are not set up to support remote employees who reside in New York. In order to be considered for employment, applicants must be currently legally authorized to work in the job location country and not require future sponsorship in order to continue working in that country.

We appreciate your interest in our company. Because of the high volume of resume flow, we may only respond to those candidates that we think will be a potential fit.

–

#LI-AE1

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

About Us:

Spreedly is the world’s leading Open Payments Platform. Founded in 2007 and headquartered in Durham, NC, the company gives mid-market and enterprise businesses the infrastructure to connect to any payment gateway, processor, or fraud tool through a single API. The platform is vendor-agnostic by design, meaning customers are never locked into a single provider and never need to rebuild their payments stack to access new capabilities.

The core business problem Spreedly solves is real and costly: global merchants face a fragmented payments ecosystem, where every new market, payment method, or fraud tool typically requires a separate, time-consuming integration. Spreedly eliminates that complexity, enabling companies to route transactions intelligently, secure cardholder data, prevent fraud, and expand into new markets without heavy engineering overhead.

Product Offering:

Spreedly provides an open payments platform. The platform’s connectivity provides payments performance. Key products and services include:

Connect— A unified API that integrates with hundreds of payment gateways, processors, and alternative payment methods worldwide, including digital wallets. Merchants access the global payments ecosystem through one connection.

Vault — A PCI-compliant secure repository for payment methods. Merchants store card data once and reuse it across any payment service, reducing PCI scope and protecting cardholder data at scale.

Optimize— Workflow-driven routing and retry logic that directs each transaction to the best-performing gateway in real time. On average, 7.9% of failed transactions succeed immediately when retried on a secondary gateway. This is where merchants recover lost revenue and increase authorization success rates.

Protect— A flexible fraud and authentication layer, incorporating advanced fraud tools and 3DS. Following Spreedly’s acquisition of Dodgeball in September 2025, fraud orchestration and payment optimization now operate within the same platform.

Resolve— Centralized management and reporting that reduces operational silos, strengthens security, and improves billing control across a merchant’s entire payment operation.

What It’s Like to Work Here:

We describe our team as “Spreedlings”: diverse, forward-thinking, and driven by a shared belief that a more open payments ecosystem benefits everyone. The company operates with a culture built on transparency, courageous collaboration, and self-driven leadership. The team values simplicity in both product and process, and approaches problem-solving with genuine curiosity.

About the Role:

We’re looking for a Business AI Operations Lead to help Spreedly transform how business teams operate by identifying high-value opportunities and translating them into practical, scalable AI-enabled workflows.

This role leads AI workflow discovery across R&D and builds prioritized solutions across R&D and other business functions. It also owns key Marketing Operations activities outside of scoring, routing, and analytics, which are managed by Revenue Operations.

The ideal candidate combines strong operational judgment with hands-on implementation skills. They can understand how work happens today, identify opportunities for meaningful improvement, and deliver practical solutions that teams adopt and continue to use.

Success in this role will be measured by the on-time delivery of prioritized workflows, improved operational efficiency, strong adoption, measurable business outcomes, and reliable processes and solutions.

Responsibilities:

R&D Workflow Discovery

• Lead AI workflow discovery across Product, Engineering, and other R&D functions.
• Partner with stakeholders to understand business needs, operational challenges, and existing processes.
• Identify opportunities where AI and automation can reduce manual work, improve execution, or increase productivity.
• Document and maintain identified R&D opportunities in the shared company AI workflow inventory for prioritization.
• Translate selected opportunities into clear requirements, success measures, and implementation plans.

Business AI Execution

• Design and build prioritized AI workflows across R&D and other business functions.
• Translate business requirements into practical solutions using approved AI platforms and shared capabilities.
• Deliver assigned solutions on time and communicate risks or delays early.
• Focus primarily on operational AI workflows that can deliver measurable business value.
• Test solutions with business users, incorporate feedback, and support successful adoption.
• Partner with the AI Enablement & Solutions Lead when initiatives require advanced architecture, reusable capabilities, or complex cross-functional design.
• Apply shared AI standards and recommended implementation patterns to assigned solutions.

Solution Ownership

• Serve as the AI build owner for assigned workflows.
• Own solution design, development, testing, launch, maintenance, and ongoing optimization.
• Partner with internal business customers to validate requirements, support adoption, and measure business outcomes.
• Develop documentation, user guidance, and training materials for delivered solutions.
• Monitor solution performance and identify opportunities for continued improvement.
• Ensure assigned workflows remain aligned with shared AI standards and company priorities.

Marketing Operations

• Own Marketing Operations activities outside of scoring, routing, and analytics.
• Manage campaign operations and configuration, nurture programs, audience segmentation, webinars, and marketing automation.
• Support data quality, source management, auditing, lead-flow execution, and operational governance in partnership with Revenue Operations.
• Optimize the marketing technology stack, including HubSpot, Salesforce, Influ2, and related platforms.
• Partner with Revenue Operations on processes and systems involving scoring, routing, analytics, and reporting.
• Ensure Marketing Operations processes and workflows remain scalable, reliable, and well maintained.

Requirements:

• 5+ years of experience in Business Operations, Marketing Operations, process improvement, automation, or a related field.
• Hands-on experience designing, implementing, and maintaining operational workflows.
• Experience using Claude or similar tools to build AI-enabled business workflows.
• Experience with APIs, low-code or no-code platforms, workflow automation, or prompt engineering.
• Experience applying AI or automation to improve business processes and productivity.
• Strong ability to translate business needs into practical, usable solutions.
• Experience with business systems, workflow automation, and modern technology platforms.
• Experience with HubSpot, Salesforce, or comparable business platforms.
• Demonstrated ability to drive adoption and organizational change without direct authority.
• Strong analytical, project-management, communication, and stakeholder-management skills.
• Ability to manage multiple priorities across different business functions.
• Strong attention to detail and commitment to reliable, maintainable execution.

Additional Skills We Value:

• Experience with n8n, Apollo, Clay, Influ2, or similar platforms.
• Experience supporting Product, Engineering, Marketing, Sales, Customer Success, or Revenue Operations.
• Experience with SQL, reporting, analytics, or data visualization.
• Experience in SaaS, fintech, payments, or another technology environment.
• Experience supporting AI workflow discovery or business process redesign.

We Offer Our US-Based Employees:

• Competitive salary + Equity
• Outstanding Medical and Dental benefits, including 100% employer-paid options
• Company-paid Life and Disability insurance
• Optional vision and supplemental insurance options, and various Flexible Spending Accounts (FSA)
• Open Paid Time Off policy + 12 weeks of paid leave for new parents
• Matching 401(k) plan (5% up to $5,000 yearly)
• $1,000 annual professional development stipend
• Monthly home working/digital lifestyle stipend, new MacBook, and one-time accessory reimbursement
• Access to company-paid professional coaching service
• Visits to HQ in Durham, North Carolina for remote employees

#LI-AE1

We champion the ethical, creative use of AI—if you’re someone who pairs human judgment with modern AI tools to work smarter and drive bigger impact, you’ll thrive here.

–

Spreedly is an equal opportunity employer. We are committed to fostering, cultivating, and preserving a culture of diversity, equity, inclusion, and belonging. We actively work to drive out even unintentional discrimination in our hiring processes via practices like blindly graded work samples, structured interviews, and diversity awareness training.

Due to the sensitive nature of what Spreedly does - handling payment data - finalist candidates must complete a successful background and reference check.

At this time Spreedly is unable to provide sponsorship for employment, and we are not set up to support remote employees who reside in New York. In order to be considered for employment, applicants must be currently legally authorized to work in the job location country and not require future sponsorship in order to continue working in that country.

We appreciate your interest in our company. Because of the high volume of resume flow, we may only respond to those candidates that we think will be a potential fit.

–

#LI-AE1

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Headquarters: Remote, Canada; Remote, United Kingdom; Remote, US

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster.

The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software.

*Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab.

An overview of this role

As an AI Transformation Owner at GitLab, you'll shape your function's AI strategy and build the solutions that deliver it. You are the person responsible for identifying where AI can fundamentally change how your org operates, partnering with your Executive Sponsor to align on the biggest challenges, and driving measurable outcomes against them.

Think of this as a product management role where the product is your org's way of working. You'll manage the full lifecycle: understanding how work flows today, deciding where AI should reshape it, prioritising what gets built and in what order, and ensuring what ships actually gets adopted. You'll also prototype solutions, configure agents, and prove what's possible before pulling in engineering support to scale it.

You will work closely with an AI Engineer who sits within the Enterprise AI team. Together you form a partnership: you bring the business context, process intelligence, and strategic prioritisation. They bring the technical depth, production-grade delivery, and architecture decisions. You'll build working solutions at the no-code and low-code layer, and partner with the AI Engineer on the right approach, tooling, and structure.

 

What you'll do

Strategy & Prioritisation

• Own your function's AI strategy, aligned with your Executive Sponsor and business priorities. Understand which metrics matter to the org, identify what will move the needle, define how you'll measure impact, and track progress over time.
• Map how work flows across your function end-to-end, including the handoffs upstream and downstream to other orgs. Identify where the real constraints are, not just the ones your team can see. Focus on the 100x problems: where could leveraging AI in a workflow let your org execute it orders of magnitude faster, or at 100x more volume than before?
• Manage intake of AI requests, ideas, and pain points from across the function, including via your Champion network. Ensure every team member has a clear route to surface what they need, rather than building independently.
• Prioritise strategically against business outcomes and executive guidance. Hold the line on priorities - we cannot change direction every two weeks - and ensure the AI Engineer's time is spent on the highest-impact work.

Adoption & Change Management

• Reimagine, not just automate. Challenge your org to think beyond injecting AI into existing workflows. Work with Enterprise AI to spot opportunities to fundamentally rethink how work gets done.
• Drive adoption and change management together with the AI Engineer. The best AI solution is worthless if nobody uses it. Create the channels, rituals, and feedback loops that make AI visible in your function: shared spaces for teams to show what they've built, regular office hours, onboarding for new hires, and celebration of wins. Own the rollout and iteration needed to make AI initiatives stick.
• Coordinate with Enterprise AI to ensure your function benefits from patterns, tools, and learnings emerging across other parts of the business.
• Build and bridge the Champion network in your function. Champions are the peer community that extends your reach beyond what you and the AI Engineer can deliver directly. From early in the role, identify and recruit Champions across sub-teams (5-10% time, formally agreed with their manager), run a regular Champion sync, host demos to the wider function, and act as their bridge to Enterprise AI. Champions are not your reports: you coordinate them, you don't manage them. Without this network, your reach is capped.

Hands-On Building & Agent Operations

• Build AI agents using no-code and low-code platforms (e.g. Glean, Workato, similar tools). Go from idea to working prototype without waiting for engineering.
• Author and iterate on skills files that define how AI agents behave. Refine instructions based on real usage and share reusable skills across the function.
• Configure MCP servers and tools, giving agents access to the business systems they need. Partner with the AI Engineer on what to connect and how to do it securely.
• Own your function's fleet of agents. Some agents will be used directly by people in your org. Those that aren't, you own. Either way, you're accountable for their performance: tracking KPIs, running evaluations after model or data changes, and iterating based on what you learn.
• Expect to rebuild. AI tools and models evolve fast. The agent you built last month may need to be replaced, not patched. You should be comfortable sunsetting your own work when a better approach emerges, and helping your org stay current rather than attached to what exists today.

What you'll bring

Business & Strategic

• Deep knowledge of your function's operations. You understand how work moves through your org, where it gets stuck, and why. You can trace a process end-to-end and explain how it connects to the teams around it.
• Strategic prioritisation skills. You've managed competing demands before and can make hard calls about what matters most. You think in terms of business outcomes, not activity.
• A product management mindset. You naturally think about intake, backlog, iteration, and adoption. You're comfortable defining success metrics and holding yourself accountable to them.
• Strong communication and influence. You'll be the person saying "not yet" to some teams and "think bigger" to others. You need the credibility and interpersonal skills to make both of those conversations land.
• Cross-functional instincts. You default to understanding how your org's processes affect and are affected by the teams around you - not just optimising in isolation.
• Experience building peer networks or communities of practice. You've recruited and sustained volunteer contributors before, whether as a guild lead, champion programme owner, or community organiser. You know how to motivate people whose time you don't directly own.

Hands-On & Technical

• Comfortable building with AI tools. You don't need to write production code, but you should be able to build a working agent, configure a skill, connect an MCP server, and troubleshoot when something isn't working. Think: power user, not software engineer.
• Ready to learn fast. Experience with or willingness to quickly pick up no-code/low-code AI platforms, prompt engineering, and agent configuration. You'll be trained on GitLab's specific tooling, but you should arrive ready to get your hands dirty.
• Strong conceptual understanding of AI capabilities - summarisation, classification, generation, automation, agentic workflows - and a commitment to staying current. The landscape shifts constantly. The tools you use today may be obsolete in weeks. You stay on top of new developments so that your org's AI strategy reflects what's actually possible, not what was possible six months ago.
• Ability to map data flows - structured and unstructured. Understand where agents need context, and figure out where humans should interface with automated workflows and at what steps.

About the team

You will partner closely with Enterprise AI within the Enterprise Technology & AI organisation, while remaining embedded in your own function. Enterprise AI provides the technical delivery capability, platforms, and patterns. You provide the business context, prioritisation, building at the no-code layer, and adoption muscle. Together, you form the core of your function's AI transformation.

The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity. Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary.

United States Salary Range$152,800—$259,200 USD

How GitLab Supports Full-Time Employees

• Benefits to support your health, finances, and well-being
• Flexible Paid Time Off 
• Team Member Resource Groups
• Equity Compensation & Employee Stock Purchase Plan
• Growth and Development Fund
• Parental Leave 

Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application.

Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process.  

Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us.

GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know during the recruiting process.

To apply: https://weworkremotely.com/remote-jobs/gitlab-ai-transformation-owner-marketing

Who we are

At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences.

Our dedication to remote-first work, and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands.

We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions!

.

See yourself at Twilio

Join the team as Twilio’s next Sr AI Architect - Conversation AI.

About the job

This position is critical to leveraging Twilio’s massive data ecosystem and unmatched communication scale to build our customer facing AI capabilities, such as Twilio Conversational Memory, Enterprise Knowledge, Behavioral Data Intelligence and many more to power the future of our customer engagement platform.

As a Sr. AI Architect for Twilio Platform, you will also influence the design and evolution of our company-wide ML/AI Ops foundation. You will set the long-term technical vision, establish architectural guardrails, and ensure strict adherence to responsible AI principles. You will drive cross-organizational initiatives, solve complex technical challenges, and elevate the technical standards across all of Twilio. Transitioning AI/ML concepts from cutting-edge research to resilient, compliant, and cost-effective production systems will be your core mission.

As a Sr AI Architect, you will lead the company as the Distinguished Engineer and AI Contextual Engineering SME, serving as the guiding authority to our Architects, driving company-wide impact, and steering Twilio’s overarching technical direction for conversational AI. In this pivotal leadership role, you will also influence the design and evolution of our company-wide ML/AI Ops foundation. You will set the long-term technical vision, establish architectural guardrails, and ensure strict adherence to responsible AI principles. By driving cross-organizational initiatives and solving complex technical challenges, you will elevate the technical standards across all of Twilio. Transitioning AI/ML concepts from cutting-edge research to resilient, compliant, and cost-effective production systems will be your core mission.

Responsibilities

In this role, you’ll:

• Define and drive a long-term AI/ML architectural vision that aligns with Twilio’s business goals, specifically focusing on how data and memory power the next generation of customer engagement.
• Own the strategic roadmap for Twilio’s ML/AI Ops platform and tooling, ensuring a unified approach to model development, deployment, and lifecycle management across all platform capabilities.
• Evaluate and implement modern LLM architectures, RAG systems, MCP/tooling frameworks, and inference optimization techniques.
• Lead architecture for agentic AI systems including orchestration, reasoning, tool usage, and contextual grounding.
• Stay current with rapidly evolving advancements in LLMs, agent frameworks, reasoning systems, and AI infrastructure.
• Transition seamlessly from high-level strategic communication with executives to deep-dive code reviews and pair programming with engineers.
• Partner closely with Product Management to turn a roadmap into a sequence of technical milestones, ensuring that technical investments always map to customer value.
• Have a ‘player-coach’ mentality, and contribute hands-on technical expertise while providing strategic direction and mentorship to the team.

Qualifications

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn’t followed a traditional path, don’t let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

Required:

• 15+ years of experience in software engineering, with at least 6+ years specifically focused on building and scaling production-grade ML systems at a platform level.
• Extensive experience with ML Ops and LLM Ops patterns, including designing and implementing rigorous evaluation metrics, automated retraining loops, and monitoring for non-deterministic AI features at scale.
• Deep expertise in the design, architecture, and deployment of production-grade ML/AI systems, including deep knowledge of transformer models, LLM orchestration, embedding models, inference optimization and vector stores.
• Deep understanding of the Context Engineering lifecycle, including semantic retrieval, contextual compression, state management across multi-turn conversations.
• Strong background in building cloud-based services using AWS, GCP, or Azure, with experience managing high-volume data and various data stores.
• Exceptional communication and collaboration skills, with a proven ability to mentor engineers, influence company wide technical strategy, product direction, and drive results across the company.
• A Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a closely related quantitative field.

Desired

• A track record of relevant publications at top ML conferences or significant open-source contributions.
• Experience designing evaluation frameworks that specifically measure context quality
• Track record of designing and implementing enterprise-scale ML/AI Ops platforms
• Experience working in a geographically distributed environment.

Location

This role will be <remote and based in the United States.

Travel

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, approximately 5% travel is anticipated to help you connect in-person in a meaningful way.

What We Offer

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

Compensation

Please note this role is open to candidates outside of California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington D.C., and Washington State. The information below is provided for candidates hired in those locations only.

The estimated pay ranges for this role are as follows:

• Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $275,840.00 - 344,800.00.
• Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $292,080.00 - 365,100.00.
• Based in the San Francisco Bay area, California: $324,480.00 - 405,600.00.
• This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave.

The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location.

Application deadline information

Applications for this role are intended to be accepted until August 30, 2026 but may change based on business needs.

Twilio thinks big. Do you?

We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That’s why we seek out colleagues who embody our values — something we call Twilio Magic. Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts.

So, if you’re ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn’t what you’re looking for, please consider other open positions.

Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

Who we are

At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences.

Our dedication to remote-first work, and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands.

We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions!

.

See yourself at Twilio

Join the team as Twilio’s next Sr AI Architect - Conversation AI.

About the job

This position is critical to leveraging Twilio’s massive data ecosystem and unmatched communication scale to build our customer facing AI capabilities, such as Twilio Conversational Memory, Enterprise Knowledge, Behavioral Data Intelligence and many more to power the future of our customer engagement platform.

As a Sr. AI Architect for Twilio Platform, you will also influence the design and evolution of our company-wide ML/AI Ops foundation. You will set the long-term technical vision, establish architectural guardrails, and ensure strict adherence to responsible AI principles. You will drive cross-organizational initiatives, solve complex technical challenges, and elevate the technical standards across all of Twilio. Transitioning AI/ML concepts from cutting-edge research to resilient, compliant, and cost-effective production systems will be your core mission.

As a Sr AI Architect, you will lead the company as the Distinguished Engineer and AI Contextual Engineering SME, serving as the guiding authority to our Architects, driving company-wide impact, and steering Twilio’s overarching technical direction for conversational AI. In this pivotal leadership role, you will also influence the design and evolution of our company-wide ML/AI Ops foundation. You will set the long-term technical vision, establish architectural guardrails, and ensure strict adherence to responsible AI principles. By driving cross-organizational initiatives and solving complex technical challenges, you will elevate the technical standards across all of Twilio. Transitioning AI/ML concepts from cutting-edge research to resilient, compliant, and cost-effective production systems will be your core mission.

Responsibilities

In this role, you’ll:

• Define and drive a long-term AI/ML architectural vision that aligns with Twilio’s business goals, specifically focusing on how data and memory power the next generation of customer engagement.
• Own the strategic roadmap for Twilio’s ML/AI Ops platform and tooling, ensuring a unified approach to model development, deployment, and lifecycle management across all platform capabilities.
• Evaluate and implement modern LLM architectures, RAG systems, MCP/tooling frameworks, and inference optimization techniques.
• Lead architecture for agentic AI systems including orchestration, reasoning, tool usage, and contextual grounding.
• Stay current with rapidly evolving advancements in LLMs, agent frameworks, reasoning systems, and AI infrastructure.
• Transition seamlessly from high-level strategic communication with executives to deep-dive code reviews and pair programming with engineers.
• Partner closely with Product Management to turn a roadmap into a sequence of technical milestones, ensuring that technical investments always map to customer value.
• Have a ‘player-coach’ mentality, and contribute hands-on technical expertise while providing strategic direction and mentorship to the team.

Qualifications

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn’t followed a traditional path, don’t let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

Required:

• 15+ years of experience in software engineering, with at least 6+ years specifically focused on building and scaling production-grade ML systems at a platform level.
• Extensive experience with ML Ops and LLM Ops patterns, including designing and implementing rigorous evaluation metrics, automated retraining loops, and monitoring for non-deterministic AI features at scale.
• Deep expertise in the design, architecture, and deployment of production-grade ML/AI systems, including deep knowledge of transformer models, LLM orchestration, embedding models, inference optimization and vector stores.
• Deep understanding of the Context Engineering lifecycle, including semantic retrieval, contextual compression, state management across multi-turn conversations.
• Strong background in building cloud-based services using AWS, GCP, or Azure, with experience managing high-volume data and various data stores.
• Exceptional communication and collaboration skills, with a proven ability to mentor engineers, influence company wide technical strategy, product direction, and drive results across the company.
• A Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a closely related quantitative field.

Desired

• A track record of relevant publications at top ML conferences or significant open-source contributions.
• Experience designing evaluation frameworks that specifically measure context quality
• Track record of designing and implementing enterprise-scale ML/AI Ops platforms
• Experience working in a geographically distributed environment.

Location

This role will be <remote and based in the United States.

Travel

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, approximately 5% travel is anticipated to help you connect in-person in a meaningful way.

What We Offer

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

Compensation

Please note this role is open to candidates outside of California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington D.C., and Washington State. The information below is provided for candidates hired in those locations only.

The estimated pay ranges for this role are as follows:

• Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $275,840.00 - 344,800.00.
• Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $292,080.00 - 365,100.00.
• Based in the San Francisco Bay area, California: $324,480.00 - 405,600.00.
• This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave.

The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location.

Application deadline information

Applications for this role are intended to be accepted until August 30, 2026 but may change based on business needs.

Twilio thinks big. Do you?

We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That’s why we seek out colleagues who embody our values — something we call Twilio Magic. Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts.

So, if you’re ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn’t what you’re looking for, please consider other open positions.

Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

Who we are

At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences.

Our dedication to remote-first work, and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands.

We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions!

.

See yourself at Twilio

Join the team as Twilio’s next Senior Principal Field Architect - AI Agents

About the job

The Senior Principal Field Engineer is a critical, highly visible leader on the Field CTO team who bridges the gap between Twilio’s product vision and our customers’ needs. In the rapidly evolving era of AI, Twilio takes an open and flexible approach: we want developers to use their preferred AI coding tools and agent builder platforms to get up and running extremely quickly with our platform of APIs across a variety of services that address many use cases.

In this P7 Distinguished Engineer role, you will be in R&D and partner with Product, Engineering, Sales and GTM teams to spearhead the launch and adoption of our AI-native platform services. You will be the field engineering linchpin ensuring that the newly launched Twilio Conversations suite and Twilio Agent Connect (TAC) integrate flawlessly with the industry’s top AI tools. Your mission is to ensure that insights from the field directly influence product strategy while actively building deep, functional partnerships with the companies driving the AI revolution. You will derisk adoption, increase partner integrations to accelerate adoption and create repeatable blueprints for mass adoption.

Responsibilities

In this role, you’ll:

• Ecosystem Engineering & Integration: Engineer seamless integrations between Twilio Agent Connect (TAC), the Twilio Conversations suite, and hyperscaler AI platforms (AWS Bedrock, Azure Foundry, GCP Vertex AI Agent Builder, and Meta’s Business Agent platform for example).
• Champion the Builder’s Mindset: Demonstrate a deep, practical understanding of modern software development. You must know how developers are using AI coding tools like Claude, Gemini, and Cursor to build conversational AI (omnichannel customer support agents, for example) on top of Twilio today and in the future.
• Strategic Partnerships: Act as a technical liaison and partnership builder with our Partner Teams with leading AI tool and cloud companies, ensuring Twilio’s APIs work perfectly within their ecosystems to accelerate our customers’ time-to-market.
• Roadmap & Vision Leadership: Present Twilio’s technical roadmap and vision to customers. Consolidate insights into structured inputs for planning to help shape R&D priorities.
• Sales & Go-to-Market Enablement: Support and provide direction to Sales and Specialist teams on the latest positioning, use cases, and technical roadmaps. Work with sales enablement to ensure teams are covering the right topics.
• Customer Discovery: Partner with the Specialist team to capture technical and business requirements with key enterprise accounts identified as design partners.

Qualifications

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn’t followed a traditional path, don’t let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

*Required:

• 10+ years of engineering experience coupled with 8+ years in enterprise technology strategy technical product management, cloud engineering, or executive consulting roles.
• Cloud & AI Expertise: Deep architectural understanding of major cloud hyperscalers (AWS, Azure, GCP) and hands-on familiarity with conversational AI, chatbots, cognitive services, and machine learning architectures and engineering practices.
• Engineering Nuance: A strong technical background to discuss complex system architectures and integrate AI technologies. .
• Strategic Thinking & Leadership: Ability to develop and execute long-term solution architectures, roadmaps, and cross-functional initiatives at an enterprise scale with significant business impact.
• Technical & Business Acumen: Exceptional communication skills to articulate complex concepts to both highly technical developers and business-focused executives.
• Customer Focus & Agility: Proven ability to advocate for customer-centric engineering practices and thrive in a fast-paced, evolving environment with comfort operating in areas of ambiguity.

Desired:

• Proven track record of supporting and enabling sales and partner ecosystems with product knowledge and GTM materials.
• Experience building modern digital customer engagement experiences using cloud and AI services to help customers identify and resolve issues.
• Advanced degree (Master’s in Computer Science, Physics, or related field), or Bachelor’s degree from an accredited university or equivalent experience.

Location

This role will be remote, but is not eligible to be hired in San Francisco, CA, Oakland, CA, San Jose, CA, or the surrounding areas.

Travel

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, approximately 20% travel is anticipated to help you connect in-person in a meaningful way.

What We Offer

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

Compensation

Please note the salary range information provided applies only to candidates residing in California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington D.C., and Washington State due to local requirements. Compensation for candidates in other locations will be discussed during the hiring process. Please note that hiring for this role is not restricted to the locations listed above.

The estimated pay ranges for this role are as follows:

• Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $284,320 - $355,400.
• Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $292,080 – $365,100.
• Based in the San Francisco Bay area, California: $324,480 - $405,600.

This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave.

The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location.

Application deadline information

Applications for this role are intended to be accepted until August 3, 2026 but may change based on business needs.

Twilio thinks big. Do you?

We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That’s why we seek out colleagues who embody our values — something we call Twilio Magic. Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts.

So, if you’re ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn’t what you’re looking for, please consider other open positions.

Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

Headquarters: San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States

 

Mercury is building a whole stack of financial tools for startups. We work hard to create dashboards with thought and simplicity. You can check out our demo dashboard at www.demo.mercury.com.

Behind every product Mercury ships is a fast-growing company: dozens of teams across engineering, product, design, data, and business functions, and hundreds of projects that require alignment across compliance, legal, partnerships, customer support, finance, and leadership. AI Ops builds the systems that keep that organization moving, helping teams move quickly without losing shared context.

In this role, you'll own Mercury's internal knowledge infrastructure: the systems and standards that make company information accurate, discoverable, and useful. You'll build and maintain a trusted context layer—a structured, living record of what teams own, are building, and know—and ensure it stays current automatically.

That context layer powers leadership reporting, planning, operational reviews, and the internal AI agents employees use every day. You'll define how information is organized, validated, and maintained across systems like Linear and Mercury's internal platforms so they function as a single source of truth.

Working closely with Engineering, who own the underlying infrastructure, you'll design the knowledge layer above it: the taxonomies, schemas, validation workflows, and automations that make company knowledge reliable for both people and AI systems.

This role sits at the intersection of systems operations, knowledge architecture, and product thinking. Success isn't measured by collecting more information, but by creating a high-signal knowledge system that helps employees find answers quickly, enables leaders to make decisions from shared context, and gives AI systems the foundation they need to operate effectively.

Mercury aims to make banking* feel secure, reliable, thoughtful, and perhaps even magical. Your job is to make the company's internal knowledge systems just as dependable.

*Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.

You will:

• Own Mercury's knowledge infrastructure: the trusted context layer that captures what every team owns, is building, and knows, along with the information architecture, taxonomy, and governance that keep it accurate, current, and useful.
• Build the knowledge layer on top of Mercury's AI infrastructure by partnering with AI Engineering to design the schemas, automations, and validation workflows that allow people and AI agents to reliably retrieve and act on company knowledge.
• Own the reporting layer that turns shared context into operational insight, including leadership reporting, roadmap views, planning dashboards, and the reporting that powers company operating cadences.
• Drive company-wide adoption of standardized systems and practices by partnering across Engineering, Product, Design, Data, Compliance, Legal, Finance, Partnerships, Customer Support, and other teams to replace fragmented documentation with trusted, structured sources of truth.
• Continuously improve how Mercury captures, organizes, and uses knowledge by identifying operational friction, building better workflows, and ensuring employees have the tooling and enablement they need to effectively work with AI.

You should:

• Have 5–8 years of experience in program or product operations, technical program management, product management, data, or similar roles where you drove company-wide systems or operational improvements.
• Think like a systems designer and knowledge architect, able to turn messy, distributed information into simple, scalable structures that people and AI systems can easily understand and trust.
• Be comfortable working with technical systems, including APIs, data models, analytics, and tools like Linear, GitHub, Metabase, and modern AI platforms, even if you aren't building the underlying infrastructure yourself.
• Have hands-on experience using AI to create leverage through workflows, automations, agents, or other practical applications, along with a solid understanding of how LLMs retrieve and consume information.
• Influence organizations through strong judgment, clear communication, and thoughtful execution, thriving in ambiguous environments where the right systems have to be invented rather than inherited.

The total rewards package at Mercury includes base salary, equity (stock options), and benefits.

Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate's experience, expertise, geographic location, and internal pay equity relative to peers.

Our target new hire base salary ranges for this role are the following:

• US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $163,000 - $203,800
• US employees outside of the New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $146,700 - $183,400
• Canadian employees (any location): CAD $154,100 - $192,600

*Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. [Please see the independent bias audit report covering our use of Covey for more information.]

#LI-JD1

 

To apply: https://weworkremotely.com/remote-jobs/mercury-ai-context-operations-lead