Product Engineer

About the role

You will own the full lifecycle of AI-powered product features from discovery through production, embedding directly with operators in sales, service, and underwriting to identify where the current distribution system breaks down and building the AI solution that fixes it before the problem is even articulated. You will treat AI tooling as a core part of the workflow, not a novelty, optimizing relentlessly for user and business impact across the stack rather than for code elegance. Each week you will ship AI-powered product features end-to-end on real systems serving real users, proving impact with metrics that compound as the AI learns from every interaction. You will move fast with new model releases and emerging capabilities, using advanced cursor and Claude Code workflows to compress development cycles and test what is newly possible on the frontier. You will collaborate closely with founders without committees or slow approval chains, taking direct ownership of outcomes by prototyping on Monday, shipping on Tuesday, and measuring results on Wednesday. Your work will run in production environments, not in demos or side projects, because the code you write is the system that sells insurance to millions of businesses. You will present clear explanations of metric changes to non-technical stakeholders, aligning product performance with business growth while iterating based on real-world feedback.

Key facts

What you'll do

• Ship AI-powered features end-to-end, owning frontend, backend, agents, and evals so that the entire stack delivers measurable business outcomes.
• Embed with operators in sales, service, and underwriting to observe workflows and uncover friction points before they become explicit problems.
• Build systems that compound value, where every decision is traced, every outcome feeds back, and the AI becomes smarter with each interaction.
• Stay on the frontier of capability by testing new model releases the same day they drop and shipping new functionality as soon as it lands.
• Move fast with AI tooling, using Cursor, Claude Code, and the next generation of workflows to manage multiple coding sessions and compress timelines that normally take weeks into days.
• Own the metric that matters, articulating impact in terms of conversion lifts, cost reductions, or performance gains rather than simply listing features shipped.
• Prove impact by setting up robust metrics, tracking results over time, and presenting clear findings to the company on what worked and why.
• Work without committee approval, building directly with founders and taking full ownership of the problem, the solution, and the business result.

Requirements

• Software engineering experience shipping production systems, with the seniority level determined during the interview process based on demonstrated impact.
• Proficiency in Python, TypeScript, or similar languages, with the ability to write clean, maintainable code that scales in production.
• Experience building and shipping AI-powered features, including LLM applications, agent pipelines, or workflow automation that serve real users.
• Ability to work across the full stack, comfortably switching between frontend, backend, and the AI decision layer without requiring deep specialization in a single lane.
• Based in San Francisco or willing to relocate to the Bay Area to align with in-office operating expectations.

Nice to have

• Voice AI or real-time systems experience that can handle low-latency interactions in production environments.
• RAG, agent frameworks, or evaluation systems that help the team measure quality and reliability of AI outputs.
• Background in operations tooling, sales technology, or workflow automation that mirrors the insurance distribution stack.
• Prior startup experience where you shipped under uncertainty, iterated quickly, and wore multiple hats to deliver outcomes.

Practical notes

• Schedule: Monday-Friday, very early morning start, in-office five days a week.
• Location requirement: Based in San Francisco or willing to relocate to support in-office collaboration.
• The role follows an intensive on-site super day where you will meet the team, sit in on live operations, and do real work side by side with current engineers.
• Apply only if you are prepared to ship code that runs a real business and measure results that affect the company's growth trajectory.