Director of Product, AI Decision Platform

Salary range is:

$157,417.86 - $240,000.00

This position is long-term incentive and bonus and/or commission eligible.

The RoleWe are building an AI-native decision platform for bodily injury claims, and we are hiring the Director of Product who will design it.

Every bodily injury claim contains hundreds of decisions. Some are exact calculations with one right answer. Some require interpreting medical evidence. Some are judgment calls a carrier reserves for its own people. For most P&C carriers, the guideposts for those decisions are spread across rules engines, manual review, and institutional memory; we are building one platform that facilitates each decision with the right method, explains it, and measures whether it was correct.

As the platform's first product lead, you will co-own the product in direct partnership with the VP of Product & Engineering. You will define what gets built, why it matters, and when it ships, while your counterpart manages the engineering team and technical execution. Together, you will scope projects and collaborate daily with engineers, eventually hiring and leading a growing team of product managers as the platform scales.

This is a design role in the fullest sense. The core architecture, the way carriers express how they want decisions handled, the standard for correctness, and the boundary between software and human judgment are all open, and all yours to shape.

Key Responsibilities:

What You'll Do

• Own the strategy, roadmap, and commercial success of a key product area from inception through market validation

• Build and ship AI-first products that guide and augment human decision-making in auto casualty claims

• Work directly with senior executives at major insurance carriers to uncover problems, test product visions, and drive business outcomes

• Architect complex decision-making frameworks that effectively balance AI capabilities, automated logic, and human oversight.

• Translate deep domain expertise including complex client workflows, regulatory guidelines, and clinical constraints, into precise, scalable engineering requirements.

• Establish rigorous evaluation standards and monitoring systems to ensure accuracy, explainability, and auditability across all system outputs.

• Rapidly prototype and validate concepts directly with key industry stakeholders to gather feedback and refine strategy prior to engineering handoff.

• Hire, mentor, and lead a growing product team, setting the foundational operating standards for product management in your area as the organization scales.

• Partner with customer success, sales, and product marketing to develop go-to-market strategy
  

What Success Looks Like

The platform will successfully drive real-world decisions for carriers, supported by measurable correctness metrics tracked across decision types and jurisdictions. Your precise specifications and rigorous evaluations will accelerate engineering velocity by eliminating ambiguity early in the development cycle. Additionally, you will have scaled the product organization by hiring and fully onboarding a productive team.

About You

You have designed a platform, not just a product. You have owned something that many enterprise customers configure differently, where the hard part was the long tail: dozens of customer variations, changing regulations, and no clean abstraction handed to you. You found the abstraction, and you can walk us through the decisions you made to get there and the ones you got wrong.

You have shipped AI into production where accuracy mattered. You know the difference between a demo that looks right and a system you can trust, and you have personally built the machinery that tells them apart: you have read hundreds of model outputs, grouped the failures, written evaluators for the errors you actually saw, and checked those evaluators against expert judgment. You treat AI as one method among several. When a calculation has one right answer, you want deterministic code, and you can explain why.

You build. When you say you built something, you mean you wrote the prompts, wired the workflow, ran the evaluation, and sat with the customer, not that you wrote the spec and someone else did the rest. You work in Cursor, Claude Code, or similar tools daily, you can read a system design doc and a codebase without translation; engineers trust your technical judgment because you are never hand-wavy.

You have gone deep in at least one complex, regulated domain (health payer, payments integrity, revenue cycle, fintech, legal, insurance, or similar) and can explain how you built that understanding. Experience in insurance claims or medical billing is a real advantage but not a requirement; evidence that you learn complex domains fast and separate essential complexity from accumulated habit is.

You are comfortable as a player-coach. You would rather solve the problem than simply manage people who solve it. You also know what good product practice looks like and how to introduce it, because you will be setting the standard for everyone who follows you.

What We're Not Looking For

• Someone who wants to manage a team more than design the system

• Someone who shapes strategy and hands a specification to engineering

• Someone for whom "the outputs look good" counts as an evaluation

• Someone who reaches for AI when a lookup table would give the right answer every time
  
  

Key Competencies
Systems design. You break a messy domain into clean primitives, decide where configuration ends and code begins, and design for the variation you know is coming without building for every variation you can imagine.

Evaluation and correctness. You can define what correct means for a decision, design a gold set with domain experts, choose between code checks, model-based judges, and human review, and report accuracy honestly, including what you don't know.

Technical contribution. You prototype agent workflows, write evaluation code, and make direct contributions to the product you own.

Trust by design. You design for explainability, auditability, source traceability, and graceful failure, and you treat human-in-the-loop controls as product surfaces rather than afterthoughts.

Enterprise customer depth. You can be credible with senior executives in a regulated industry, as well as with with the operators who do the daily work.

Team building. You have hired or mentored PMs and can describe the standard you held them to.

Requirements:

• 8+ years of product management experience in enterprise software, with significant time owning a platform or core system used by many enterprise customers

• Shipped at least one AI-driven product in production, including the evaluation and monitoring behind it

• Deep experience in at least one complex, regulated vertical

• Hands-on prototyping and technical contribution using AI coding tools

• Track record of working directly with enterprise customers and senior stakeholders to shape product direction

• Experience hiring, mentoring, or leading product managers

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