Job description

The Forward Deployed Engineering (FDE) team within Business Innovation & AI (BIA) is looking for a Senior Technical Program Manager who builds. FDE embeds directly with teams across Amazon Global Operations Services (GOS), co-builds with them from day one, and ships working AI-powered solutions. Engagements range from short builds to multi-quarter programs. The impact here is internal: you build for the GOS org, not for external customers. We increasingly look for opportunities to replace manual processes and web-based interfaces with AI agents, so a lot of what you build will be agentic. This is an FDE role first, with a data engineering edge. The core of the job is building AI and agentic solutions embedded with operational teams. On top of that, you own the team’s data and data-engineering strategy and infrastructure, the pipelines and architecture and data-quality decisions our AI work depends on. This is a builder role. We’re looking for people who are already shipping AI solutions with the current generation of tooling, not people who are newly exploring AI or have only done some prompt engineering. The engineers who do well here are hands-on with agentic harnesses like Claude Code, Kiro, and Codex, and are plugged into the AI builder community closely enough to know what changed this month. Key job responsibilities Build AI & Agentic Solutions, Embedded (the primary work) - Embed with GOS operational teams, co-build from day one, and ship AI-powered solutions that change how work gets done - Look for opportunities to replace manual processes and web-based interfaces with AI agents, and build those agents end to end - Build with the current AI tooling yourself, including agentic harnesses (Claude Code, Kiro, Codex), LLM application frameworks, and RAG, and take prototypes to production Program Delivery - Drive the planning, coordination, and delivery of FDE’s AI programs, managing risk and dependencies without relying on direct authority - Turn ambiguous operational problems into shipped solutions, and own the longer-horizon programs where the answer takes more than one build cycle Data & Data-Engineering Strategy (the DE edge) - Own the team’s data and data-engineering strategy and infrastructure: the architecture, technology choices, and roadmap our AI work depends on - Make the calls on how operational data becomes AI-ready, and keep data quality, lineage, and freshness where the team can trust it - Connect source data to what the customer actually needs: find the right source, get the subscription in place, and build the pipeline that keeps it flowing - Make and defend the opinionated architecture calls (lakehouse vs. warehouse, batch vs. streaming, how far to normalize a domain), grounded in each use case Raising the Bar - Define the reusable patterns and standards that raise the bar for the whole team, and mentor engineers on them A day in the life You start the morning embedded with an operations team, working through a manual workflow you’re replacing with an agent. By mid-morning you’re building against it with current tooling and putting the next iteration in front of them. In the afternoon you switch to the data side, making the call on how a new data domain gets modeled and subscribed into the platform so the agent has what it needs. You close the day reviewing a teammate’s design against the patterns you set, and re-cutting the roadmap for a program that has two quarters left to run. About the team Business Innovation & AI (BIA) finds the hardest, highest-value problems across Amazon Global Operations Services and builds AI-powered solutions that measurably change how work gets done. Forward Deployed Engineering (FDE) is BIA’s technical execution arm: a small, senior team with high autonomy and a bias for shipping. We embed with operational teams in the GOS org, co-build from day one, ship working solutions, and hand scalable patterns off to the broader organization. We don’t just automate the existing process; we redesign the work around what AI and agents make possible. - 5+ years of technical program management experience - Experience developing, deploying and managing AI products at scale - Knowledge of data engineering pipelines, cloud solutions, ETL management, databases, visualizations and analytical platforms - Experience with SQL and Python scripting - Bachelor's degree in computer science, engineering, mathematics or equivalent, or Bachelor's degree or above in computer science, engineering, analytics, mathematics, statistics, IT or equivalent - Experience with AWS data services (S3, Glue, Athena, Redshift, or an equivalent cloud data stack) - Experience driving technical programs across multiple teams without direct authority - Experience defining and driving an analytics roadmap - 5+ years of data modeling experience - A track record of shipping bespoke AI and agentic solutions from scratch, and active engagement in AI builder communities - Experience building AI agents that replace manual or UI-driven workflows - Familiarity with Amazon’s internal data ecosystem (Andes, data subscriptions, and getting access to source data across orgs) - Fluency with the current GenAI tooling landscape (Amazon Bedrock, agent frameworks, LLM-powered workflows) - Experience with Infrastructure as Code (CDK, CloudFormation, Terraform) - Experience with real-time or streaming data infrastructure (Kinesis, Kafka, Flink) - Experience mentoring engineers and defining reusable patterns that scale beyond a single team Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit amazon.jobs for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at amazon.jobs . USA, TN, Nashville - 141,300.00 - 191,100.00 USD annually USA, WA, Bellevue - 148,700.00 - 201,200.00 USD annually

Requirements

Must-haves

Key job responsibilities
Build AI & Agentic Solutions, Embedded (the primary work)
Embed with GOS operational teams, co-build from day one, and ship AI-powered solutions that change how work gets done
Look for opportunities to replace manual processes and web-based interfaces with AI agents, and build those agents end to end
Build with the current AI tooling yourself, including agentic harnesses (Claude Code, Kiro, Codex), LLM application frameworks, and RAG, and take prototypes to production
Program Delivery
Drive the planning, coordination, and delivery of FDE’s AI programs, managing risk and dependencies without relying on direct authority
Turn ambiguous operational problems into shipped solutions, and own the longer-horizon programs where the answer takes more than one build cycle
Data & Data-Engineering Strategy (the DE edge)
Own the team’s data and data-engineering strategy and infrastructure: the architecture, technology choices, and roadmap our AI work depends on
Make the calls on how operational data becomes AI-ready, and keep data quality, lineage, and freshness where the team can trust it
Connect source data to what the customer actually needs: find the right source, get the subscription in place, and build the pipeline that keeps it flowing
Make and defend the opinionated architecture calls (lakehouse vs. warehouse, batch vs. streaming, how far to normalize a domain), grounded in each use case
Raising the Bar
Define the reusable patterns and standards that raise the bar for the whole team, and mentor engineers on them
A day in the life
About the team
5+ years of technical program management experience
Experience developing, deploying and managing AI products at scale
Knowledge of data engineering pipelines, cloud solutions, ETL management, databases, visualizations and analytical platforms
Experience with SQL and Python scripting
Bachelor's degree in computer science, engineering, mathematics or equivalent, or Bachelor's degree or above in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
Experience with AWS data services (S3, Glue, Athena, Redshift, or an equivalent cloud data stack)
Experience driving technical programs across multiple teams without direct authority

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Keywords to mirror

aillmsqlpythonaws

Platform: amazon
Effort: medium

Benefits

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Health Insurance

Dental

Vision

401(K)

Paid Time Off

Parental Leave