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About This Role
DESCRIPTION
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Amazon Web Services (AWS) is seeking an experienced Partner Development Manager to accelerate the adoption of AWS AI and Agentic AI tools across our Worldwide Public Sector National Systems Integrator (NSI) partner ecosystem. This position is part of the AWS Worldwide Public Sector (WWPS) Partner Organization. Our team works at the intersection of cloud technology and the public sector mission—partnering with National Systems Integrators (NSIs) to deliver innovative solutions for government, defense, education, nonprofit, and healthcare customers. We drive adoption of AWS services by enabling our partners to build differentiated capabilities that accelerate our customers’ missions.
In this role, you will develop and execute strategies that drive NSI partners to embed AI\-driven development practices into their customer delivery engagements, internal solution development, and operational tooling—while also building joint go\-to\-market motions that bring agentic AI solutions to market for partner product development teams and end users.
You will be a trusted advisor to partners across all levels—from technical delivery teams building with AWS AI services to C\-suite executives evaluating AI strategies and finance leaders assessing ROI. You will define solution\-oriented offerings, develop pipeline, and drive adoption by selling to, through, and with NSI partners. The ideal candidate combines deep technical fluency in software development and AI/ML, with the business acumen to articulate the financial case for AI transformation to partner executives. Critically, the ideal candidate has a builder mentality that thrives on creating new motions from scratch.
Key job responsibilities
- Drive pipeline and revenue through joint go\-to\-market motions with NSI partners to bring agentic AI solutions to WWPS end\-customers, creating new demand and accelerating adoption of AWS AI services.
- Accelerate partner AI adoption by developing strategies that drive NSI partners to embed AWS Agentic AI tools (e.g., Amazon Bedrock, Amazon Kiro, Amazon SageMaker) into their customer delivery engagements, solution offerings, and operational tooling.
- Define solution\-oriented joint offerings with NSI partners that package AWS Agentic AI capabilities into repeatable, scalable solutions for public sector end customers across all WWPS verticals.
- Enable AI\-driven development practices across partner delivery organizations—championing modern AI development lifecycle approaches that reimagine traditional software engineering processes through AI\-powered inception, construction, and operations workflows.
- Engage partners to articulate the process transformation benefits and financial ROI of adopting AI tools for delivery execution, demonstrating how agentic AI accelerates engagement timelines, reduces cost\-to\-deliver, and improves solution quality.
- Develop business cases and financial models that quantify the return on investment of AI tool adoption for partner and customer organizations, enabling data\-driven decisions on AI transformation investments.
- Serve as an internal AI subject matter expert aligned to the WWPS partner organization, advocating for partner AI capabilities and connecting partner needs to AWS product and field teams.
- Scale proven adoption motions by identifying successful partner AI adoption patterns and replicating them across the broader NSI partner ecosystem.
- Engage multi\-level stakeholders across partner and customer organizations—from technical delivery leads and development teams to C\-suite executives and finance leadership—articulating technical capabilities, solution value, and financial impact of agentic AI adoption.
- Collaborate cross\-functionally with solution architecture, product management, partner management, field sales, and account teams to create joint revenue opportunities and remove blockers to customer AI adoption through partners.
- Identify and develop new market opportunities for agentic AI solutions across WWPS verticals, working with partners to translate customer needs into joint offerings that drive adoption and revenue growth.
BASIC QUALIFICATIONS
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- 6\+ years of Go\-To\-Market, Business Development, Sales, or Consulting experience
- 2\+ 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
- 3\+ years of developing, negotiating and executing business agreements experience
- Experience developing strategies that influence leadership decisions at the organizational level
- Experience explaining complex technical concepts to various business and technical audiences
- Bachelor's degree
- Experience building and analyzing cost/benefit scenarios and business cases and communicating results throughout the organization
- Familiarity with AI\-driven development lifecycle methodologies and agentic AI frameworks
PREFERRED QUALIFICATIONS
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- 2\+ years of software development experience
- Experience selling to or working with public sector organizations (federal, defense, state/local, education, nonprofit, healthcare)
- 2\+ years of technology consulting experience (delivery, solution architecture, or advisory)
- Experience working with National Systems Integrators or large consulting partners
- Experience defining and launching new partner solutions, offerings, or go\-to\-market programs
- Experience with AWS AI/ML services (Amazon Bedrock, Amazon Kiro, Amazon SageMaker) or equivalent cloud AI platforms,
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.
Pursuant to the San Francisco 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, 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: $188K across 140 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 3,708 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 $216,175 based on 270 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($191K) sits 11% below the category median. Disclosed range: $162K to $220K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Amazon Web Services AI Hiring
Amazon Web Services has 73 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager, Research Scientist, Data Scientist. Positions span New York, NY, US, Austin, TX, US, Jersey City, NJ, US. Compensation range: $129K - $342K.
Location Context
AI roles in New York pay a median of $220,000 across 1,045 tracked positions.
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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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