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About This Role
DESCRIPTION
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Do you have the business savvy, GenAI background in the Startup space, and sales skills necessary to help position AWS as the cloud provider of choice for customers? Do you love building new strategic and data\-driven businesses? Join the Startup Organization (SUP) team as GTM Executive GenAI Startups!
We're seeking a customer\-obsessed builder to join our Startup Organization (SUP) team as GTM GenAI Startups lead.
The GenAI team drives revenue, adoption, and growth from the largest and fastest\-growing GenAI startups through strategic partnerships and effective GTM strategies.
We work backwards from our customer’s most complex and business critical problems to build and execute go\-to\-market plans that turn AWS ideas into multi\-billion\-dollar businesses. GenAI teams include sales, business development and technical solutions architecture. As part of GenAI SUP team you'll provide expertise across the entire life cycle of an GenAI startups’ initiative, from developing ideas for new services to accelerating the adoption of established businesses. We pride ourselves on thinking big, delivering exceptional results for our customers, and working across AWS as \#OneTeam.
The GenAI team helps customers adopt our newest and most advantageous technologies. We are technology specialists and a team dedicated to helping Startups scale quickly and cost\-effectively on AWS. We want Startups to grow better when they choose AWS and we make it easier by recommending the right technologies and then by helping Startups get up and running quickly.
This position specifically is part of the GenAI team, where you will be a Technical Business Developer that helps Startups adopt AWS’ technologies with a focus on Sagemaker, Bedrock, EC2 among others.
AWS Global Sales drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched technology, and unwavering support. We dive deep to understand each customer's unique challenges, then craft innovative solutions that accelerate their success. This customer\-first approach is how we built the world's most adopted cloud. Join us and help us grow.
Key job responsibilities
- Design and execute bespoke GTM strategies with AWS's top generative AI startups
- Engage with C\-Suite executives, developers, and technical architects to: (1\) Explore and establish strategic partnerships (2\) Secure GenAI lighthouse customers (3\) Drive top\-line revenue
- Develop and maintain deep understanding of AWS offerings (particularly Sagemaker, Bedrock, and EC2\) to identify partnership opportunities
- Create strategic documentation for both startups and AWS leadership
- Serve as a trusted business \& technical advisor to our top Generative AI startup partners
- Lead/oversee cross\-functional execution of GTM strategies
About the team
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.
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.
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.
Inclusive Team Culture
AWS values curiosity and connection. Our employee\-led and company\-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
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
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- 5\+ years of professional or military experience
- 5\+ years of developing, negotiating and executing business agreements experience
- 5\+ years of working with Core Cloud Technology Services, including, but not limited to Compute, Edge, Hybrid, Security, and/or Networking experience
- 5\+ years of working with Business Application Technologies, including, but not limited to End User Compute (EUC), Supply Chain, Contact Center as a Service, Consumer Data Applications, Encrypted Communications, and/or Communication Developer Services experience
- 5\+ years of solving problems with technology in the Healthcare/Life Sciences Industry experience
- 5\+ years of solving problems with technology in the Media \& Entertainment Industry experience
- 5\+ years of solving problems with technology in the Global Financial Services Industry experience
- 5\+ years of solving problems with technology in the Telecommunications industry experience
- 5\+ years of solving problems with technology in the Automotive \& Manufacturing industries experience
- 5\+ years of solving problems with technology in the Energy \& Utilities industries experience
- 5\+ years of Go\-To\-Market, Business Development, Sales, or Consulting experience
- 5\+ years of working with Advanced Compute technologies including, but not limited to: Accelerated Compute, High Performance Compute, Visual/Spatial Compute, and/or IoT. experience
- 5\+ years of working with Enterprise Application Modernization and Migration technologies, including, but not limited to, Mainframe, Serverless, Containers, or Cloud Operations experience
- 5\+ years of working with Data \& AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
- 5\+ years of working with Data \& AI related technologies, including, but not limited to, AI/ML (Artificial Intelligence/Machine Learning), GenAI (Generative AI), Analytics, Database, and/or Storage experience
- 5\+ years of in program management, workforce strategy development, or metrics\-driven decision making experience
- Bachelor's degree
- Knowledge of publisher ad tech stacks and/or advertising technology
- Experience developing strategies that influence leadership decisions at the organizational level
- Experience managing programs across cross functional teams, building processes and coordinating release schedules
- Experience selling enterprise software or cloud\-based applications
- Experience explaining complex technical concepts to various business and technical audiences
- Experience presenting to both technical and non\-technical executive audiences
- Experience leading complex, multi\-year initiatives that may be cross\-functional and/or span business and technology
PREFERRED QUALIFICATIONS
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- Master's degree in business, data science, public administration, finance, engineering, human resources, or related field, or PMP certificate
- Experience interpreting data and making business recommendations
- Experience identifying, negotiating, and executing complex legal agreements
- Experience designing, implementing, and scaling workforce development programs across large\-scale operations, including forecasting workforce needs and leveraging analytics to drive program decisions
- Experience interpreting data and making business recommendations across leadership and cross\-functional teams
- Experience using analytical tools for workforce metrics and reporting
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 \- 162,700\.00 \- 220,200\.00 USD annually
Salary Context
This $162K-$220K range is above the median for AI Product Manager roles in our dataset (median: $189K across 161 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 3,823 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Amazon Web Services, 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 $213,800 based on 583 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($191K) sits 10% below the category median. Disclosed range: $162K to $220K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Amazon Web Services AI Hiring
Amazon Web Services has 78 open AI roles right now. They're hiring across AI/ML Engineer, AI Agent Developer, Research Scientist, AI Product Manager. Positions span Seattle, WA, US, San Francisco, CA, US, Arlington, VA, US. Compensation range: $177K - $295K.
Location Context
AI roles in New York pay a median of $211,000 across 2,643 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, 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 Engineering Manager roles lead at $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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.
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