Product Manager - AI

Own the roadmap to improve document/data extraction accuracy against defined targets, including major build-vs-improve calls on the underlying approach, in partnership with ML/engineering.

Define what "accurate enough to trust" means for each use case, and track progress against it on a live, shared metric.

Agent runtime & governance.

Own product requirements for the runtime that lets AI agents take actions inside the product.

Direct experience shipping ML/AI-backed product where trust and accuracy were the product, not a feature bullet. You’ve defined a precision/recall bar and held engineering…

Working fluency in what “governance” means for an AI system in production: audit trails, explainability, human-in-the-loop design, policy enforcement…

Comfortable owning a roadmap with genuine capability uncertainty and communicating that uncertainty honestly to stakeholders instead of smoothing it over.

Platform-PM instincts: default to “how do I make this self-serve” over “how do I build this feature for one team” Says no to scope…