Interested in this AI Product Manager role at Amazon.com?
Apply Now →Skills & Technologies
About This Role
DESCRIPTION
---------------
AWS Hardware Engineering Services owns the design, planning, delivery, and operation of all AWS global compute systems. 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.
You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
Amazon Web Services (AWS) Hardware Engineering team creates compute and storage server designs for Amazon’s web services. Our engineers work with leading edge technologies, solve challenging problems, influence the industry’s roadmaps, and develop new and unique solutions that are ahead of the pack. We work in an environment that fosters innovation and creativity. We encourage and invest in new directions and new ideas that will serve our customers better. We sometimes fail, but we learn from such failures and we improve. It is because of the team and our constant focus on the customers, that we are able to develop creative and new designs that set the standards on performance, quality, cost, and operational excellence.
What you will do: As a member of the Server Hardware Engineering team you will own and lead the design and development of server products utilizing a wide range of design and manufacturing partners.
You will work closely with our customers to understand their technical needs and business goals, leveraging your experience with server design and the knowledge of various teams to architect the solutions that we will deploy at scale.
To deliver your products you will work with an interdisciplinary team of component, firmware, test, qualification, and integration engineers, and lead our design and manufacturing partners to bring these servers to the data center. After launch you will oversee the fleet of servers you develop, monitoring their quality and how they are meeting the customer requirements.
This is a fast\-paced, intellectually challenging position, and you’ll work with thought leaders in multiple technology areas. You’ll have high standards for yourself and everyone you work with, and you’ll be constantly looking for ways to improve your products' performance, quality, and cost. We’re changing an industry, and we want individuals who are ready for this challenge and want to reach beyond what is possible today.
Why you will love it: You will work directly with a talented team of engineers and product owners across the company to create next\-generation hardware. You will have a direct impact on your customer's success, drive the development of the Cloud, and have a meaningful impact on Amazon's success. You will be part of a growing, fast paced, and fun team.
Key job responsibilities
You will be a technical leader solving complex problems. You will decompose big difficult server system testability, reliability and diagnosis problems into straightforward tasks, components or features that you will lead to deliver yourself and through others in parallel. You will use combination of hardware, software, system designs, x86 architecture, processes, diagnosis and operations knowledge.
A day in the life
Working with a variety of job roles (SDEs, SDETs, Hardware Engineers, TPMs, Managers, Principals) and groups (AWS Hardware Engineering, EC2, other AWS services) through server conception, design, test, launch, and operations. Driving high quality and reliability into future/new designs for AWS server solutions for AWS Cloud.
About the team
\*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.
\*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.
\*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.
\*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 (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
\*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.
BASIC QUALIFICATIONS
------------------------
- 4\+ years of non\-internship professional software development experience
- 4\+ years of deploying and operating in a Linux/Unix environment experience
- 4\+ years of systems development in an IT or data center environment experience
- 3\+ years of programming with at least one modern language such as C\+\+, C\#, Java, Python, Golang, PowerShell, Ruby experience
- 2\+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience
- 2\+ years of systems design, software development, operations, automation, and process improvement experience
- Experience leading the design, build and deployment of complex and performant (reliable and scalable) software solutions in production
PREFERRED QUALIFICATIONS
----------------------------
- 3\+ years of development/programming/scripting language (Python/Java/Bash/Perl) experience
- Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations
- Experience taking a leading role in building complex software or computing infrastructure that has been successfully delivered to customers
- Experience debugging, integrating, and validating Cloud Computing servers.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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, CA, Cupertino \- 173,900\.00 \- 235,200\.00 USD annually
USA, WA, Seattle \- 151,200\.00 \- 204,600\.00 USD annually
Salary Context
This $151K-$204K range is above the median for AI Product Manager roles in our dataset (median: $174K across 475 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 26,159 AI roles we're tracking, AI Product Manager positions make up 2% of the market. At Amazon.com, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $204,600 based on 532 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($177K) sits 13% below the category median. Disclosed range: $151K to $204K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Amazon.com AI Hiring
Amazon.com has 488 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager, Data Scientist, Research Scientist. Positions span New York, NY, US, Seattle, WA, US, Arlington, VA, US. Compensation range: $52K - $342K.
Location Context
AI roles in Seattle pay a median of $223,600 across 678 tracked positions. That's 22% above the national median.
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.