Principal Product Manager, AI Products

Komodo Health is a healthcare technology company that combines de-identified real-world patient data with innovative algorithms to build software applications for healthcare insights. The Principal Product Manager will define and build the next generation of Komodo's AI-powered product suite, developing new products, shaping the portfolio, partnering with customers and go-to-market teams, and leading small engineering pods.

Responsibilities:

• Own the thesis for what customers touch. Study how they actually work, decide what should exist, and revise the argument as models improve
• Build first versions with AI tools and platform primitives. Bring engineering in to scale what shows value, and drop what does not
• Work inside customer environments when the problem calls for it, scope in real time while contracts are being negotiated, and treat deployment as part of the product
• Propose and defend the shape of the growing portfolio. As the new generation lands, you decide what the existing solutions become
• Package for the field. Partner with sales and marketing on what we sell, run the market analysis behind it, and make sure every new product can be positioned, enabled, and sold
• Set the pattern. Your architecture and your build habits become how the surface pods around you work

Requirements:

• Builds the first version. You will show us something you built, not something you managed, this is evaluated in the interview
• AI native at product depth. You can reason at a low level about the AI products you intend to ship: context and grounding, evals and quality gates, agent behavior, and cost. Using chat tools to work faster is the baseline everywhere, so it earns nothing here
• Comfortable inside customer environments and contracting cycles, with the judgment to commit responsibly in real time
• Zero to one at Principal  scope. 10+ years in product, including at least one product you conceived and shipped that earns real revenue today. We will ask what existed before it, and what was retired to make room for it
• Excellent written communication. Your reasoning gets adopted because it is clear
• Healthcare or regulated data experience (claims, EHR, patient journeys, provider analytics), or a track record of getting fluent fast in a comparably complex data domain like supply chain, energy, or financial data
• Time at a company through a platform transition
• Experience retiring a product without losing its customers
• Experience interacting with, managing, or building with AI agentic workflows