Principal Product Manager, Technical ES, Mission AI

Description

Some of the most consequential AI work in the country happens where the internet does not reach. As the Principal Product Manager for Mission AI, you will decide what that work becomes. You will own the product strategy for AI capability delivered on one of the largest AI infrastructure programs AWS has ever taken on: a dedicated, accredited GPU environment where strong open-weight and Amazon models are adapted to a national security customer's own data and problems.
There is no established product playbook for this. Public benchmarks, model hubs, and package repositories are not available inside the environment, compute is a fixed on-premises fleet, and the customer's mission needs are still being defined. You will work directly with the customer's technical leaders, analysts, and operators to find the problems worth solving, then turn them into clear requirements that scientists and engineers can build against. You will decide what ships first, what "better than the base model" has to mean before we claim it, and how capability moves from the lab to the people who rely on it. You will also set product direction for the program's infrastructure product manager, so platform and AI capability run as one roadmap.
You join at the start. The lab's first scientists are being hired now, and the decisions you make in your first year shape both what the program delivers and what it is asked to deliver next.
The candidate selected must obtain and maintain a security clearance at the TS/SCI with polygraph level. Upon start, the selected candidate will be sponsored for a commensurate clearance for each government agency for which they perform AWS work.
Key job responsibilities
- Own the product vision and multi-year roadmap for mission AI capability: adapted models, evaluation suites, and the inference and agentic services the customer's engineers integrate into their mission systems.
- Run discovery with customer technical leads, analysts, and operators to find and rank the highest-value mission use cases, and write the narratives (PR/FAQ, strategy documents) that drive investment decisions.
- Define what success means for each use case before work starts, partnering with the lab's science leads to set evaluation standards and the margin a model must clear to count as an improvement.
- Translate mission needs into functional and technical requirements, and make the trade-offs between capability, compute budget, schedule, and accreditation constraints.
- Own launch readiness inside the accredited environment: technical readiness, independent verification and validation, accreditation and authorization gates, operational handoff, and customer adoption.
- Shape future task orders: build the evidence-backed business case and scope for the next wave of mission AI work, partnering with program, contracts, and finance.
- Be accountable for outcomes: track adoption, mission impact, and delivery against goals, and report progress in program and executive reviews.
- Own customer engagement across the service lifecycle: adoption, optimization, problem resolution, and evolution of each capability once it is in mission use. Own escalations on the services you ship and dive deep with engineers to resolve them.
- Influence the engineering roadmaps of the customer's technical decision makers, so their mission systems are built to take advantage of what the lab delivers next.
- Write architecture and technical requirements documents for the lab's services, and contribute to engineering design reviews on how they are built, served, and scaled.
- Partner with Tech Business Development, Solutions Architects, ProServe, and engineering leaders inside and outside AWS to drive service success.
- Set product direction for and mentor the program's infrastructure product manager, and help hire and develop the product team as the program scales.
A day in the life
You start the morning reading the overnight evaluation results with the lab's scientists, checking whether an adapted model has cleared the bar you agreed with the customer for a priority mission task. Mid-morning, you work with customer analysts on a workflow they run every day, looking for the step where a model would change their outcome rather than just their speed. After lunch, you review the infrastructure team's serving plan and decide whether the next release can meet its accreditation gate on schedule or needs to be re-scoped. You close the day drafting the business case for a capability the customer has not asked for yet, but that the evidence says they will need in the next task order.
About the team
The Mission AI Model Lab is the science team behind AWS's Mission AI program. We take existing models and make them useful for problems that matter to national security, working on dedicated AI infrastructure built for exactly that. This lab is purpose-built and these are among its first scientists, so the people who join now help shape how it works and what it builds. We sit where frontier-model research meets national security delivery, and we value invention on genuinely new problems, evaluation we can defend, and plain talk with the people who rely on what we build.
Why AWS
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AWS Infrastructure Services (AIS)
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Inclusive Team Culture
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Work/Life Balance
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Diverse Experiences
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