About the Role
PlayOn Sports is seeking a Principal Product Manager, Artificial Intelligence & Computer Vision to take end-to-end ownership of a new product line focused on AI and computer vision capabilities. This role involves strategy, launch, and ongoing operational health. It is a product leadership position in a dynamic area of technology, where you will set the vision, make critical trade-offs, and drive outcomes across engineering, data, design, and external partners. Initially an individual contributor role, it holds the expectation to grow a small team as the product line matures.
This role is ideal for someone who thrives in ambiguous, high-impact environments, has a proven track record of bringing early-stage bets to market, and is energized by enhancing the discoverability and meaning of high school sports moments.
The Outcomes You Will Deliver
- A production-grade AI content pipeline, live across multiple sports.
- A sport-agnostic game data model that serves as PlayOn's canonical source of game intelligence.
- An operating model that functions efficiently without requiring your constant intervention in critical paths.
What You Will Own
Strategy and Roadmap
- Set and own the multi-year vision for the product line, ensuring alignment among business leadership, engineering, partners, and vendors on scope, sequencing, and success metrics.
- Translate business goals, including fan engagement and growth, content quality and coverage, and school retention, into a concrete product strategy spanning computer vision capabilities, data pipelines, and fan-facing surfaces.
- Define and drive product line KPIs such as accuracy benchmarks, processing latency, content coverage, and downstream product adoption.
Partner & Vendor Leadership
- Own the strategic relationship with our computer vision and AI vendors, setting agendas, aligning roadmaps, and holding partners accountable for delivery commitments.
- Evaluate new CV capabilities, including object detection, OCR, region-of-interest framing, tracking, and automated highlight segmentation, and make informed decisions on integration timing and rationale.
- Drive integrations with vendor engineering teams, resolving complex problems and accelerating capability adoption.
Cross-Functional Leadership
- Partner with Data Engineering to build a sport-agnostic game data model that accommodates various sports, game formats, broadcast configurations, and data sources.
- Influence cross-product roadmaps to ensure fan and school-facing surfaces evolve in pace with our AI pipeline and generate critical feedback loops for modeling priorities.
- Provide Operations and Support teams with the necessary visibility and tooling to triage and resolve content delivery issues without requiring engineering escalation.
Operational Ownership
- Build the operating model for the product line, encompassing sport-specific configurations, fallback handling, and quality review workflows, and evolve it with product scaling.
- Close the loop between output quality (human review, fan signals, partner feedback) and upstream model or configuration improvements.
- Own end-to-end health, surfacing risks early, resolving dependencies, and ensuring transparency around content delivery, timing, quality, and coverage.
What You'll Bring
Required
- 8+ years in product management, technical product management, or a leadership role driving complex cross-team initiatives end-to-end.
- A proven track record of leading a significant company initiative where you were accountable for the outcome, working across multiple engineering teams, external partners, and business stakeholders.
- Working fluency with AI/ML concepts, understanding the capabilities and limitations of modern ML systems, reasoning about model quality tradeoffs, and engaging in technical discussions with ML engineers and vendors.
- Strong data fluency, comfortable with reading and writing SQL, interpreting quality metrics, and reasoning about schema design and pipeline tradeoffs.
- Experience owning external partner relationships at a strategic level, shaping integration contracts, holding partners accountable, and escalating effectively.
- Excellent communication, including crisp product writing, clear executive presence, and the ability to build alignment across technical and non-technical audiences.
- High tolerance for ambiguity; a proven instinct for creating structure and momentum in early-stage problem spaces.
Preferred
- Experience with live video streaming infrastructure or media processing pipelines (encoding, segmentation, metadata extraction).
- Familiarity with computer vision capabilities relevant to sports (object tracking, OCR, scene segmentation, highlight detection).
- Background in sports media, sports data, or adjacent domains (prep sports, broadcast, sports tech).
- Exposure to modern data stacks (Snowflake, dbt, Hightouch) and event-driven data architectures.
- Experience working with external sports data platforms (MaxPreps, NCAA data feeds, or similar) as data sources or integration targets.