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DESCRIPTION
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Prime Video is seeking a Principal Product Manager Technical to drive the vision, strategy, and execution of our Machine Learning platform and infrastructure, powering personalization, discovery, and customer and content intelligence at global scale.
In this role, you will own the strategy and roadmap for foundational platforms across Data, ML, and Measurement, enabling teams to rapidly build, experiment, and productionize machine learning solutions. Your mission is to enable ML builders to move from idea to production faster by removing bottlenecks across the ML lifecycle, from data ingestion and feature engineering to model training, deployment, and experimentation, so teams can iterate faster while providing robust measurement capabilities that shorten iteration cycles and consistently improve customer experiences.
You will operate in highly complex domains including recommendation systems, real\-time inference, large\-scale distributed training, LLM infrastructure, and partner closely with engineering and science leaders to influence architecture, drive adoption, and deliver measurable business outcomes.
Key job responsibilities
- Define and drive the multi\-year vision and roadmap for ML platform and infrastructure supporting personalization, discovery, content intelligence, and emerging GenAI experiences
- Develop and own the data platform strategy, delivering clean, curated datasets that encode business logic and provide science teams with trusted, model\-ready data foundations
- Build end\-to\-end ML tooling and pipelines that enable ML builders to discover datasets, ideate modeling approaches, conduct research and experimentation, and seamlessly productionize models from prototype to production
- Support large\-scale model training, real\-time inference, and compute optimization across CPU and GPU to ensure models perform efficiently at production scale
- Define and evolve the feature store strategy, supporting both online and offline data serving while minimizing online/offline skew to ensure consistency between training and serving environments
- Own the developer experience for ML builders by delivering self\-service tools, reusable components, and standardized workflows that increase productivity, reduce operational overhead, and improve cost efficiency, scalability, and availability
- Enhance the measurement platform to monitor model performance in production, track input and output metric alignment, and ensure models deliver intended business outcomes
- Influence senior leadership and cross\-functional stakeholders to align on platform strategy, investment priorities, and trade\-offs
- Drive adoption of platform capabilities across teams by ensuring solutions are intuitive, reliable, and measurably better than existing workflows
About the team
Prime Video is a first\-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios\-produced series and movies; licensed fan favorites; and programming from Prime Video add\-on subscriptions such as Apple TV\+, Max, Crunchyroll and MGM\+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads.
Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best\-in\-class digital video experience.
As a Prime Video technologist, you’ll have end\-to\-end ownership of the product, user experience, design, and technology required to deliver state\-of\-the\-art experiences for our customers. You’ll get to work on projects that are fast\-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people.
We’ll look for you to bring your diverse perspectives, ideas, and skill\-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you!BASIC QUALIFICATIONS
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- 7\+ years of end to end product delivery experience
- 4\+ years of technical product or program management experience
- Bachelor's degree
- Experience with feature delivery and tradeoffs of a product
- Experience owning/driving roadmap strategy and definition
- Experience leading engineering discussions around technology decisions and strategy related to a product
- 3\+ years of working with Data \& AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
- Deep understanding of MLOps, model training, evaluation metrics and data pipelines.
PREFERRED QUALIFICATIONS
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- Experience in project management methodologies, business analysis, or process improvement
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware
- Familiarity with recommendation systems is a bonus
- Fluency in technology alternatives with ability to weigh pros and cons of different technical approaches
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, NY, New York \- 197,900\.00 \- 267,800\.00 USD annually
USA, WA, SEATTLE \- 179,900\.00 \- 243,400\.00 USD annually
Salary Context
This $197K-$267K range is above the 75th percentile for AI Product Manager roles in our dataset (median: $187K across 164 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 4,133 AI roles we're tracking, AI Product Manager positions make up 5% 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 in Demand for This Role
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 $213,800 based on 610 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($232K) sits 9% above the category median. Disclosed range: $197K to $267K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Amazon.com AI Hiring
Amazon.com has 114 open AI roles right now. They're hiring across Research Scientist, AI/ML Engineer, AI Agent Developer, Data Scientist. Positions span New York, NY, US, Seattle, WA, US, Reading, MA, US. Compensation range: $129K - $300K.
Location Context
AI roles in New York pay a median of $211,000 across 2,760 tracked positions. That's 5% 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 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 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 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (106) are outnumbered by mid-level (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, and the 90th percentile reaches $307,500. 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 Safety roles lead at $274,200 median, while Prompt Engineer roles sit at $140,000. 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: Python (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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
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