Senior Product Manager, AI Data Platform

MGT Insurance•San Francisco, CA

1d•$190,000 - $300,000

About The Position

MGT is the first AI-driven, neo-insurer focused on evolving commercial P&C insurance for the brokers and small business owners. By combining the expertise of industry veterans with state-of-the-art technology, we are ushering in the next evolution of commercial insurance and working to move the industry forward through the use of modern technology, better processes, and a rock-star team. We seek visionary leaders who thrive in dynamic, entrepreneurial settings, and excel in autonomous roles. MGT’s AI Data Platform is the engine for our Agentic Underwriting: the vendor data, AI web search, extraction, and scoring that runs behind every quote MGT produces. We're hiring a Senior Product Manager to wake up every day thinking about driving quality results and expanding our datasets in tight coordination with the Insurance product team. You own and deliver the vendor stack, the quality and hit rate, and telemetry and evals to prove it. This is not a roadmap-and-jira role. Product and engineering lanes are merging at MGT, and product talent operates fluidly across strategy, data, design, and engineering. PMs that succeed at MGT embrace end-to-end execution and lean into our comparative advantage: agility. You will write compelling PRDs and then execute, directly contributing code, analyzing data in our warehouse, and own results from concept through to post go live.

Requirements

You have shipped meaningful work (beyond simple prototypes) with an AI engineering tool (Claude Code, Codex, Devin, etc.) and can show the commits.
You have 5+ years of experience at a firm that achieved scale, ideally InsureTech, FinTech, or Consulting.
You build things directly. Nobody is on an island at MGT, but everyone ships.

Nice To Haves

Evals are your native language. You've built evaluation harnesses for LLM or retrieval systems and can talk about precision, recall, and cost tradeoffs.
You've run a data or API vendor stack. You have owned third-party data integrations, measured their quality, and made the call to add or remove one.
Engineering background. You wrote code the old fashioned way pre-AI, and are using the latest tools to increase your impact.
Curiosity about the AI search landscape. You have opinions, backed by experiments, on the current AI web search and extraction options.
Growth stage experience. MGT is a small, high-accountability organization and that's a plus for you.
References from peer department managers (Engineering, Data, Underwriting) that loved working with you.

Responsibilities

Manage our data and AI web search vendors as a portfolio: cost per successful enrichment, hit rate, field-level quality, latency, and contract terms. Onboard new vendors, run bake-offs with real evals, and kill or renegotiate underperformers on the numbers.
Instrument every vendor call end to end. Build (yourself, in Python/TypeScript) an agent that monitors hit rate, drift, outages, and quality regressions across the pipeline and flags them before ops or underwriting notice.
Stay current on AI web search and retrieval options (native model search tools, search APIs, crawlers, structured extraction) and know which one wins for which entity type and why, with evals to back it.
Decide which new signals move loss ratio, bind rate, or underwriting speed, and sequence them. Make crisp build-vs-rent calls and defend the unit economics.