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DESCRIPTION
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We are seeking a customer\-obsessed product manager to build CX experiences that enable AI Agents to transact on behalf of Amazon customers. This PM will own the end\-to\-end strategy for agent authentication and authorization, and delegation—ensuring that when an agent shops, pays, or takes action for a customer, it's both secure and frictionless.
This team has a "Work Hard, Have Fun, Make History" attitude. On a typical day, you might deep dive into agent transaction metrics to understand conversion drop\-offs, define consent and spending\-limit controls that give customers confidence, partner with Agentic Commerce and Payment teams on integration architecture, consult with top engineers and designers at Amazon on novel delegation models, or explore radical new approaches to trust and identity in an agent\-first world. You will be surrounded by people who are incredibly smart, passionate about Identity, and believe we are only scratching the surface of what AI agents can do to help customers everywhere.
Do you want to help define the future of how AI agents act on behalf of Amazon customers—browsing, comparing, purchasing, and managing orders—while keeping customers in control? Can you help Amazon create compelling, trust\-building experiences where customers confidently delegate shopping tasks to intelligent agents?
Our team is known internally as the Identity Services team. We own the systems that authenticate hundreds of millions of customers across Retail, Alexa, Prime Video, and Amazon Pay. Now we're extending that foundation to agent\-mediated commerce: defining how agents prove who they act for, what they're allowed to do, and how customers grant, monitor, and revoke that authority.
Mentorship and Career Growth:
Our team is dedicated to supporting new team members. We have a broad mix of experience levels and Amazon tenures, and we're building an environment that celebrates knowledge sharing and mentorship. Our PMs truly enjoy mentoring and onboarding new team members through one\-on\-one mentoring and thorough, but kind, doc reviews. We care about your career growth. We take your career goals and objectives into account when deciding ownership areas—helping each team member develop into a better\-rounded PM and enabling them to take on more complex features and services in the future.
Key job responsibilities
1\. Customer\-Centric Strategy: Start with the customer and work backwards. Deeply understand how customers want to delegate shopping tasks to AI agents—what makes them feel safe, in control, and delighted. Use those insights to define and evolve the Agent Identity and Agent Transaction strategy, ensuring every feature earns customer trust and removes friction from agent\-assisted shopping.
2\. Customer Experience Definition: Write requirements from the customer's perspective. Define what a customer sees, feels, and controls when an agent acts for them—from granting permission, to reviewing an agent's cart, to revoking access. Produce user stories that articulate the customer's mental model of trust, not just system requirements. Partner with Legal and Privacy to ensure compliance enhances (not hinders) the customer experience.
3\. Roadmap Planning: Prioritize ruthlessly based on customer impact. Sequence initiatives—consent experiences, spending controls, agent authorization, and transaction transparency—by asking "which capability would customers miss most?" Deliver a consistent cadence of releases that measurably improve how easily and confidently customers let agents shop on their behalf.
4\. Cross\-Functional Customer Advocacy: Represent the customer's voice across Identity, Agentic Commerce, Payments, and Fraud teams. Influence partner teams to adopt shared standards that put customer transparency and control at the center of agent transactions. Ensure no team's technical decision degrades the end\-to\-end customer experience.
5\. Measure What Matters to Customers: Define and monitor metrics that reflect customer outcomes—task completion rates, time saved through agent delegation, customer confidence scores, opt\-in and retention rates, and friction points that cause customers to revoke agent access. Use these signals to continuously improve the experience and close gaps between what customers expect and what agents deliver.
BASIC QUALIFICATIONS
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- 8\+ years of product or program management, product marketing, business development or technology experience
- Bachelor's degree
- Experience with feature delivery and tradeoffs of a product
- Experience owning/driving roadmap strategy and definition
- Experience with end to end product delivery
- Experience contributing to engineering discussions around technology decisions and strategy related to a product
- Experience technical product management
PREFERRED QUALIFICATIONS
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- Experience working directly with Engineers on product enhancements
- Experience in project management methodologies, business analysis, or process improvement
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, WA, Seattle \- 179,900\.00 \- 243,400\.00 USD annually
Salary Context
This $179K-$243K range is above the median for AI Product Manager roles in our dataset (median: $185K across 167 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 4,317 AI roles we're tracking, AI Product Manager positions make up 4% 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 $217,100 based on 471 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. Disclosed range: $179K to $243K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Amazon.com AI Hiring
Amazon.com has 122 open AI roles right now. They're hiring across AI/ML Engineer, Research Scientist, AI Product Manager, AI Software Engineer. Positions span Seattle, WA, US, Santa Clara, CA, US, New York, NY, US. Compensation range: $128K - $338K.
Location Context
AI roles in Seattle pay a median of $228,700 across 516 tracked positions. That's 6% 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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