About The Position

We are building Protege to solve the biggest unmet need in AI — getting access to the right training data. The process today is time intensive, incredibly expensive, and often ends in failure. The Protege platform facilitates the secure, efficient, and privacy-centric exchange of AI training data. Solving AI’s data problem is a generational opportunity. We’re backed by world-class investors and already powering partnerships with some of the most ambitious teams in AI. The company that succeeds will be one of the largest in AI — and in tech. We’re a lean, fast-moving, high-trust team of builders who are obsessed with velocity and impact. Our culture is built for people who thrive on ambiguity, own outcomes, and want to shape the future of data and AI. You will own how Protege understands, represents, and surfaces its data supply—both on-platform and off-platform. You’ll build a unified system of truth for what data exists, what’s accessible but not ingested, what partners can provide, and how supply is discovered and deployed across deals. Your work replaces institutional knowledge and spreadsheets with durable product primitives and sets the foundation for eventual self-service.

Requirements

  • PM experience in data platforms, marketplaces, catalogs/search, or supply-side systems
  • Strong information architecture instincts and durable abstraction design
  • Comfortable driving cross-functional alignment across Product, Engineering, Partnerships, and Data teams

Responsibilities

  • Build our Internal Data Catalog
  • Define the data model across title, asset, and partner levels.
  • Establish a clear state model (e.g., ingested, accessible, in pipeline, linked/enriched).
  • Own search and discovery across modalities; set metadata standards with Data Lab + Engineering.
  • Ensure catalog state is auditable and resilient to refreshes, moves, and deletions.
  • Represent Off-Platform Supply
  • Create structured visibility into partner supply not yet ingested (potential, cadence, modality coverage, volume estimates).
  • Enable GTM to scope deals based on available + accessible supply—not only what’s already in-platform.
  • Partner Systems & Enablement (make relationships scalable)
  • Provide visibility into partner inclusion in deals, utilization trends, and inventory footprint.
  • Reduce partner back-and-forth caused by unclear system truth.
  • Partner with Partnerships to ensure relationships are supported by scalable system representations
  • Cross-Functional Alignment
  • Work closely with:
  • Privacy, Rights & Trust: represent data eligibility and constraints
  • Data Access & Delivery: to ensure discoverable supply is deliverable
  • Solutions Architecture: to identify catalog gaps surfaced by deals
  • Engineering: owns ingestion execution and infrastructure
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