Senior Product Engineer (US) (up to $190k)

About the role

This company is rebuilding the financial infrastructure of fertility care. By bundling treatments like IVF and egg freezing into fixed-rate packages and absorbing the financial downside when treatments are unsuccessful, they take on the clinical risk that usually falls entirely on patients. Backed by top-tier global venture firms and partnering with hundreds of clinics nationwide, they sit at the intersection of predictive underwriting, clinical operations, and consumer fintech.

As a Senior Product Engineer, you will own the central orchestration engine that coordinates care navigation, real-time risk pricing, and clinic integrations across lenders, insurers, and clinical teams. This is a role for an engineer who builds core domain infrastructure: writing the state machines, data pipelines, and production-grade LLM agents that execute back-office workflows autonomously. It is not a seat for tweaking front-end landing pages or wrapping brittle wrappers around external APIs.

Responsibilities

• Architect and scale state machines and backend workflows coordinating fragmented data between clinics, lenders, insurance carriers, and patients.
• Build and maintain the real-time underwriting engine that evaluates clinical data to accurately price treatment packages against predicted outcomes.
• Integrate autonomous LLM agents directly into internal operations to handle complex, asynchronous operational workflows rather than passive conversational interfaces.
• Design systems that enforce HIPAA and SOC 2 data isolation and auditability as first-class architectural constraints.
• Translate ambiguous clinical and financial requirements into robust, simple services designed for resilience over cleverness.

Requirements

• 5+ years of full-stack software engineering experience in high-growth startup environments, ideally with sustained tenure seeing a product scale from zero to one.
• Backend-leaning mastery in Python, with deep experience architecting state machines, asynchronous workflows, and integrations between incompatible systems.
• Demonstrated experience building within strict regulatory or compliance boundaries where data privacy is an engineering invariant, such as HIPAA, SOC 2, or PCI.
• AI-assisted development tools like Cursor, Claude Code, or Codex are an integral, daily part of how you ship production code, not an occasional experiment.
• Based in the US with authorization to work without sponsorship.