Principal Product Manager, Technical ES, Mission AI

Amazon is hiring a Principal Product Manager, Technical ES, Mission AI in Arlington, United States. It pays $181k-$245k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this AI product manager role is Builds AI ●●●●: the job is building AI systems.
The listed pay starts close to the typical AI product manager posting on Level.
Tools and skills the posting cites include GPU, product strategy and AI infrastructure.
Level lists 20,000+ other open roles at Amazon.
The role was posted in the last few days.

AI in this role

Own the product strategy and roadmap for mission-critical AI capabilities and GPU environments for national security customers at AWS.

GPU

product-strategyai-infrastructuremodel-evaluationagentic-servicesrequirements-gathering

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
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

AWS Infrastructure Services (AIS)
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.

Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Basic qualifications

- 7+ years of working as a Technical Product Manager experience
- 5+ years of technical (software development, network development, IT, other related) experience
- Experience delivering large-scale SaaS, PaaS or LaaS products where you are responsible for the full product lifecycle, from concept through GTM (go to market)

Preferred qualifications

- 7+ years of technical (software development, network development, IT, other related) experience

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 https://amazon.jobs/content/en/how-we-hire/accommodations 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 https://amazon.jobs/en/benefits.

USA, VA, Arlington - 181,100.00 - 245,000.00 USD annually

How we rate this

Principal Product Manager, Technical ES, Mission AI at Amazon rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Principal Product Manager, Technical ES, Mission AI is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $181k-$245k a year.
The role is based in US, VA, Arlington.
The job was posted on November 11, 2026.
Seniority: executive.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Product StrategyAI InfrastructureModel EvaluationAgentic ServicesRequirements GatheringGPU

Also common in AI product manager jobs at this level

LLM AI agents Generative AI Machine learning

Pay

This job starts at: $181k
Typical AI product manager job: $178k

This posting starts close to the typical AI product manager job. See AI product manager jobs

Questions you could be asked

Tell me about a project where product strategy was part of your work. What did you do?
Tell me about a project where ai infrastructure was part of your work. What did you do?
Tell me about a project where model evaluation was part of your work. What did you do?
Tell me about a project where agentic services was part of your work. What did you do?
Tell me about a project where requirements gathering was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Product Strategy, AI Infrastructure, Model Evaluation, Agentic Services, and Requirements Gathering. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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