This is not a purely technical role. It is about structuring the domain knowledge that sits underneath the product: deciding what the system should know, how it is organized and retrieved, and how it stays current as the platform scales across clubs, leagues, and portfolios.
You bring a background in information architecture or knowledge engineering and want to apply that expertise where it directly shapes how an AI product thinks. You will work closely with our top B2B clients and our internal expert network to capture complex domain knowledge, structure it for retrieval, and hold the editorial bar that keeps the corpus sharp, trusted, and actually used.
- Knowledge model & taxonomy
Own the domain ontologies, tagging schema, and per-sport / per-business-model relevance logic that every agent retrieves against. This is the structural backbone of the platform - Knowledge lifecycle Design
Govern discovery, extraction (interviews, AI-led interviews, document mining), curation, validation, and retirement, including the give-to-get contribution logic that incentivizes expert input - Cross-tenant governance
Define sharing tiers and confidentiality rules at club, league, and portfolio level and translate them into concrete access and approval workflows - Corpus curation
Build out the shared knowledge corpus and the domain-specific knowledge bases behind each agent, starting with Sponsor Acquisition and Pricing/Yield, in close collaboration with subject-matter experts - Quality & freshness
Own review cadences, source provenance, conflict resolution between contributed assets, and the metrics that prove the corpus is improving over time - Collaboration with the AI team
Partner with engineers and product to design knowledge structures that work for chunking, embeddings, and retrieval, not just for human readers