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Fanatics Commerce is the global leader in licensed sports merchandise, operating a vertically integrated platform that designs, manufactures, and delivers officially licensed apparel, jerseys, headwear, and collectibles for major leagues, teams, and events worldwide. With more than 900 e-commerce sites and a global omnichannel presence across digital, in-venue, and retail, Fanatics Commerce reaches fans in over 180 countries and powers official fan experiences for many of the world's most iconic sports properties.
At Fanatics, we bring our BOLD Leadership Principles to life every day - building championship teams, obsessing over fans, acting with entrepreneurial speed, and delivering with a determined and relentless mindset.
Staff Product Manager, AI Platform Adoption & Growth
As we continue to scale our global platform, the Staff Product Manager, AI Platform Adoption & Growth will play a critical role in driving adoption and business impact of Fanatics Commerce's AI platform.
ROLE OVERVIEW
Fanatics Commerce is building an AI platform that makes it easier for teams to build, deploy, and scale AI-powered agents and tools across the organization. The Staff Product Manager, AI Platform Adoption & Growth owns the adoption and growth of that platform, identifying where teams struggle, removing friction from onboarding through production, and turning recurring customer needs into platform improvements. This role partners with business and technology teams, fellow AI platform PMs, and engineering leaders so that customer demand and adoption data shape the platform roadmap. The Staff Product Manager, AI Platform Adoption & Growth delivers business and fan impact through BOLD leadership and execution excellence, leveraging data, automation, and AI-enabled insights.
HOW WILL YOU DRIVE IMPACT
Success is measured by the ability to deliver results through BOLD capabilities and measurable outcomes.
Team & Leadership Impact (Build Championship Teams)
- Build alignment across product, engineering, business, and senior leadership on the actions required to accelerate AI platform adoption, without relying on formal authority
- Partner with the globally distributed AI platform PM team, including peers focused on AI/agentic solution capabilities and the platform's core control plane, and with engineering leaders to ensure adoption data and customer demand inform platform priorities
- Route validated opportunities to the appropriate PM and engineering owners so delivery does not depend on a single person
Fan & Customer Impact (Obsessed with Fans)
- Develop a deep understanding of internal customers, their workflows, and their pain points, and learn why teams adopt, struggle with, or move away from the platform
- Own and continuously improve the customer journey from initial engagement through onboarding, first value, production deployment, and sustained usage
- Partner with business and technology teams to define problems, desired outcomes, and potential value where AI can improve products, processes, and customer experiences
- Help teams demonstrate and communicate the value they achieve through the platform
Innovation & Problem Solving (Limitless Entrepreneurial Spirit)
- Rapidly validate promising AI opportunities through lightweight prototypes, experiments, and proofs of concept
- Determine whether an opportunity fits existing platform capabilities, requires a new platform capability, or is better suited to a business-specific solution
- Identify recurring needs where reusable platform capabilities can unlock adoption across multiple teams
- Evaluate emerging AI technologies and patterns for meaningful potential for Fanatics Commerce
Ownership & Execution (Determined & Relentless Mindset)
- Own the adoption strategy for Fanatics Commerce's AI platform and define the metrics that demonstrate successful adoption, activation, time-to-value, sustained usage, and business impact
- Identify and remove barriers to adoption across onboarding, platform capabilities, documentation, tooling, and operating processes
- Develop repeatable mechanisms and programs that help more teams adopt and scale their use of the platform
- Own the operating rhythm and narrative with senior leadership, communicating progress, adoption barriers, emerging opportunities, and areas requiring additional investment
AI & DIGITAL CAPABILITY
We are building a future-ready organization. This role is expected to:
- Apply AI and technology to improve efficiency, quality, and outcomes
- Use data and digital tools to inform decisions and enhance performance
- Demonstrate curiosity and adaptability in adopting new technologies and ways of working
- Contribute to a culture of innovation and continuous improvement
CAPABILITIES & EXPERIENCE YOU BRING
Required Qualifications:
- Significant product management experience with a track record of owning ambiguous, high-impact problems and driving outcomes through influence rather than authority
- Demonstrated success growing adoption of a platform, product, tool, or capability across a complex organization
- Strong customer discovery skills and the ability to connect customer problems, product decisions, adoption, and measurable business outcomes
- Deep familiarity with modern AI/LLM application patterns, and enough understanding of agent architectures, tool calling, MCP-style protocols, and platform trade-offs to partner credibly with engineers
- Exceptional communication skills, with the ability to create clarity from complexity and engage engineers, product teams, business leaders, and senior executives
- Strong product judgment and first-principles thinking, with the ability to cut through ambiguity, challenge assumptions, and make thoughtful trade-offs
- Nice to have: experience building or growing internal developer platforms, infrastructure, or enterprise technology products; experience with agent frameworks, MCP servers, or orchestration platforms; experience in e-commerce, sports, or consumer technology
WORK LOCATION
Hybrid: The primary place of performance of this role is the Company's office located in Redwood City, CA subject to the Company's current hybrid work policy. This role currently requires in-office presence (Tuesday, Wednesday, Thursday).
At Fanatics, we operate with a BOLD mindset—We Build Championship Teams, we're Obsessed with Fans, we embrace a Limitless Entrepreneurial Spirit, and we approach every challenge with a Determined & Relentless Mindset. If you're ready to contribute to a dynamic, fast-paced environment that thrives on collaboration and growth, we want you to be part of our team.
At Fanatics, we operate with a BOLD mindset - We Build Championship Teams, we're Obsessed with Fans, we embrace a Limitless Entrepreneurial Spirit, and we approach every challenge with a Determined and Relentless Mindset. If you're ready to contribute to a dynamic, fast-paced environment that thrives on collaboration and growth, we want you to be part of our team.
ABOUT US
Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect, and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans; a global partner network with approximately 900 sports properties, including major national and international professional sports leagues, players associations, teams, colleges, college conferences and retail partners, 2,500 athletes and celebrities, and 200 exclusive athletes; and over 2,000 retail locations, including its Lids retail stores. Our more than 22,000 employees are committed to relentlessly enhancing the fan experience and delighting sports fans globally.
ABOUT THE TEAM
Fanatics Commerce is a leading designer, manufacturer, and seller of licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods. It operates a vertically-integrated platform of digital and physical capabilities for leading sports leagues, teams, colleges, and associations globally – as well as its flagship site, www.fanatics.com*.*
Fanatics Commerce has a broad range of online, sports venue, and vertical apparel partnerships worldwide, including comprehensive partnerships with leading leagues, teams, colleges, and sports organizations across the world—including the NFL, NBA, MLB, NHL, MLS, Formula 1, and Australian Football League (AFL); the Dallas Cowboys, Golden State Warriors, Paris Saint-Germain, Chelsea FC, and Tokyo Giants; the University of Notre Dame, University of Alabama, and University of Texas; the International Olympic Committee (IOC), England Rugby, and the Union of European Football Associations (UEFA).
At Fanatics Commerce, we infuse our BOLD Leadership Principles in everything we do:
- Build Championship Teams
- Obsessed with Fans
- Limitless Entrepreneurial Spirit
- Determined and Relentless Mindset
By submitting your application, you agree to our terms of service and acknowledge you have read our Candidate Privacy Policy.
Fanatics will never ask candidates for money, banking information, or other sensitive personal information as part of the interview process. If you receive a suspicious message claiming to be from Fanatics recruiting, please do not respond and report it here*.*
Salary Context
This $180K-$225K range is above the median for AI Product Manager roles in our dataset (median: $194K across 123 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 9,079 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Fanatics, 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 $220,200 based on 947 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($202K) sits 8% below the category median. Disclosed range: $180K to $225K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Fanatics AI Hiring
Fanatics has 1 open AI role right now. They're hiring across AI Product Manager. Based in Redwood City, CA, US. Compensation range: $225K - $225K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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