Product Manager, Search and AI

FanDuel•Atlanta, GA

3d•$94,000 - $129,250•Hybrid

About The Position

FanDuel is looking for a Product Manager to help build the search and AI-assisted bet-building experience at the heart of our sportsbook. This role sits within our Emerging Experiences pillar and spans two connected areas: core search—how millions of customers find markets, teams, players, and events—and AceAI, our AI-powered product that helps customers navigate betting decisions with intelligence and confidence. We work in small, autonomous pods—each a focused team of engineers and AI agents oriented around a specific customer problem. You'll work across multiple pods, driving initiative-level execution and keeping delivery on track across priority streams. You'll operate within a broader Advanced Search area led by a Lead PM who sets overall vision and strategy; your job is to translate that direction into well-scoped, well-executed quarterly outcomes. This is a role for someone who operates independently, is comfortable making good decisions with imperfect information, and is ready to grow into broader strategic ownership. If you've shipped search or AI-native features in consumer apps, can move fast, and want to work on a product that changes how fans interact with sports betting, this role is for you. In addition to the specific responsibilities outlined above, employees may be required to perform other such duties as assigned by the Company. This ensures operational flexibility and allows the Company to meet evolving business needs.

Requirements

Bachelor’s degree preferred
Minimum 3+ years' experience as a product manager or similar role required; 4-5 years typical for strong candidates
Demonstrated experience building search, discovery, or AI-powered features in consumer-facing apps—relevance tuning, query understanding, NLP integrations, recommendation systems, or similar
Proven ability to operate independently on initiative execution: scoping, planning, and delivering across multiple priority streams within a quarter
Solid experimentation fundamentals—able to design tests, reason about metrics, and connect product decisions to commercial outcomes (conversion, engagement, retention)
Comfortable in a fast-moving, AI-native environment—familiar with AI tooling and able to direct AI-assisted workflows as part of normal delivery
Strong operator mentality: decisive, unblocking, and effective at keeping multiple pods moving in parallel
Proven track record of shipping products that users love, with measurable outcomes
Knowledge and implementation experience of modern product practices and experimentation strategies
Strong quantitative skills and comfort with data
Excellent critical thinker and collaborator
Exceptional written and verbal communication skills

Responsibilities

Lead multiple pods—small, focused teams of engineers and AI agents—each oriented around a specific search or AI discovery problem
Set clear direction for each pod: define the problem, own prioritization, and make the calls needed to keep teams moving
Work hands-on with engineers and designers daily writing clear specs, removing blockers, and driving decisions without escalating unnecessarily
Advance the core search experience—query understanding, relevance, ranking, results presentation, and filtering—continuously improving how customers find what they're looking for
Drive the AceAI product forward, identifying where AI-assisted guidance creates the most value for customers and translating that into well-defined, shippable features
Identify user problems and opportunities within your area through research, data analysis, and competitive review
Define success criteria for each pod's work; track and report objectively on outcomes post-launch
Use A/B experimentation to validate hypotheses and drive continuous improvement across pods
Leverage AI tooling and agents effectively as part of how your pods operate— comfortable directing AI-assisted workflows alongside human engineers
Contribute to the broader Advanced Search area roadmap discussions with well-reasoned proposals grounded in user insight and commercial impact
Maintain deep knowledge of how search and AI discovery experiences work across consumer apps and bring that context into your pods' decisions
Collaborate across engineering, design, analytics, data, and operational functions to ensure smooth releases and post-launch optimizations
Communicate clearly and proactively with stakeholders on pod progress, blockers, and learnings