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Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Mountain View, CA, USA; San Francisco, CA, USA.### Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 10 years of experience in business development, partnerships, management consulting, or product management.
- Experience managing agreements or partnerships.
### Preferred qualifications:
- MBA or Master's degree in a related field.
- Experience working in the identity or agentic space.
- Experience communicating complex information to executives and external stakeholders.
- Experience working with a global team and cross\-functional stakeholders.
- Experience leading global developer\-focused product partnership programs and have developed/implemented scaled GTM developer adoption programs and engaged the ecosystem.
- Ability to identify, structure, negotiate, and execute strategic partnerships with key industry players with excellent communication and presentation skills.
About the job
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As part of the Education, Research and Core (ERC) Partnerships organization, we drive collaborations across the innovation arc—from early\-stage research to scale—to solve fundamental technology challenges using AI. Within this organization, the Core AI Partnerships team focuses on enabling safe, frictionless sign\-in and agentic experiences across first\- and third\-party platforms, unlocking personalized user journeys, and mitigating emerging AI privacy, safety, and security risks.
In this critical role, you will act as the Global Lead to advance and accelerate partner ecosystems for Core AI workstreams, specifically focusing on Core Experience, Identity, and Sign in with Google. You will collaborate closely with Google's Core platform team to help users feel in control of their personalization experiences while building a cohesive ecosystem across products.
You will be working closely with Product and Engineering teams to guide key initiatives, developing robust go\-to\-market strategies, engaging strategic partners, designing developer adoption programs, and leading high\-impact product and research agreements end\-to\-end. To succeed, you will collaborate with cross\-functional leads across Product, Engineering, gTech, Marketing, Legal, and regional teams.
We are looking for a positive, collaborative team player with strong relationship\-building, negotiation, and project management skills who is excited to shape Google's future in AI and contribute to high\-performing, and fun team culture.
The Global Partnerships organization is responsible for exploring new opportunities with Google's partners. Google’s Global Partnerships team works with a wide range of partners to bring the best of Google to power their business. The Global Partnerships team supports Google’s own Product teams with essential partnerships to help Google’s user experiences in advertising, Search, Assistant, Maps, Travel, Shopping, Payments and more. Teams create product\-enabling partnerships, go\-to\-market strategies and incubate business growth for a variety of products.Individual pay is determined by factors including job\-related skills, experience, and relevant education or training.
US: $176000 \- $256000 (USD) \+ 20% bonus target \+ equity \+ benefits
Learn more about benefits at Google.Responsibilities
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- Develop and execute a comprehensive global partnerships strategy for the Core Experience Product Area, focusing specifically on driving growth for the Access Everywhere and Identity teams.
- Lead Google Identity’s growth strategy through direct partner engagement, creative marketing activation programs, and negotiating first\-of\-its\-kind custom incentive deals to expand our ecosystem's reach.
- Manage the global partner pipeline end\-to\-end, including developing new opportunities, setting acquisition goals, and managing a global team to successfully meet our strategic goals.
- Build collaborative relationships with key internal stakeholders to align cross\-functional teams and co\-develop product strategy and objectives.
- Cultivate a deep understanding of the Identity and Account Security landscape, conduct rigorous market research to identify emerging trends and become the team's go\-to domain expert.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
Salary Context
This $176K-$256K 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 Google, 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: $176K to $256K.
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.
Google AI Hiring
Google has 134 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer, AI Agent Developer, Research Scientist. Positions span Sunnyvale, CA, US, New York, NY, US, Mountain View, CA, US. Compensation range: $144K - $365K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 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 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.
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