Staff Platform Manager (Conversational Products)

About the role

Join our team as a Staff Platform Manager for Conversational Products. In this high-stakes role, you will own the platform that determines how our AI Assistant reasons, retrieves, and responds. You will set the product direction, work with production data, build new capabilities, define success metrics, and own launch readiness for major model and platform changes. You will also diagnose architectural problems, author production behavior artifacts, and drive engineering and data science decisions. This position requires strong executive communication, hands-on technical depth, and a track record of scaling impact through others. Key missions: Ownership of the platform that determines how the AI Assistant reasons, retrieves, and responds, including the evaluation systems that keep it safe and accurate at scale.. Defining what a correct, complete resolution looks like for each kind of user problem, and getting engineering, policy, and knowledge partners aligned around that definition.. Diagnosing architectural problems, authoring the artifacts that become production behavior, and helping drive engineering and data science decisions alongside key partners. Profile: - Comfort owning an ambiguous, cross-cutting mandate that spans several teams' focus areas, and the influence to drive alignment accordingly - Strong executive communication: can lead with the decision and the ask, and adjust the narrative to the audience - 9+ years building technology products, with at least 5 in product management or a closely related technical role (engineering, data science, or applied research) from which you owned product direction - A strong sense for great user experience, including how latency, tone, and trust shape an AI interaction - Hands-on technical depth. You read and debug prompts, understand ML and engineering constraints, and are comfortable personally authoring the artifacts that shape production behavior - A track record of scaling your impact through others: setting a clear bar, assigning owners, and holding them to it - Radical thinking paired with strong execution: can envision a system meaningfully better than today and articulate the path to get there - Depth in LLM evaluation. You have designed, calibrated, or certified automated model-based evaluations, and can turn a vague quality signal into diagnostic, measurable components - Data fluency. You can work directly with production data, validate an analysis end to end, and know when a result looks wrong, whether or not you write the query by hand - Direct experience shipping generative AI or ML products to production, ideally including retrieval-augmented generation, agentic or function-calling architectures, and evaluation systems