The Problem
36 million businesses in America need insurance—it's not optional. 77% are underinsured. 40% have no coverage at all. The distribution system failed them: too slow, too opaque, too confusing.
Over 90% of commercial insurance is still human-led. We're building the inverse: 90%+ AI-led, pushing toward the higher 90s. Not by patching legacy workflows—by building AI that makes humans more effective, improves the customer experience, and eliminates friction at every step.
We're adding ~1,000 customers per month. We've grown 100x since last year. We're looking to do even more this year—and that's why we're hiring.
You'll ship AI-powered product features end-to-end. Real systems, real users, real revenue—the same week you write the code.
The Thesis
Turning judgment into compute isn't a one-time project. It's a constant hunt for leverage. New models drop monthly. What was impossible in January is table stakes by June. Someone needs to be on the frontier—figuring out what's newly possible and applying it before anyone else does.
The best product engineers here don't just write features. They embed with the operators who live inside the systems—sales, service, underwriting—find where things break, and build the AI-powered solution before anyone else notices the problem. Your code doesn't sit in a repo. It runs the business.
The Role
You're a full-stack engineer with applied-AI fluency. Frontend, backend, agents, evals—you move across the stack because the problems don't respect stack boundaries. You optimize for user and business impact, not code elegance. You treat AI tooling as a core part of the workflow, not a novelty.
You work directly with founders. No committee. No approval chain. You build it, you ship it, you own the outcome. Prototype Monday, ship Tuesday, measure Wednesday. If it works, push to production. If not, try something else.
We are hiring product engineers across all levels, which we determine during the interview process.
What You'll Do
Ship AI-powered features end-to-end — Frontend, backend, agents, and evals; you own the whole thing, not a slice
Embed with operators — Sit with sales, service, and underwriting; find what's broken before they tell you
Build systems that compound — Every decision gets traced; every outcome feeds back; the AI gets smarter with each interaction
Stay on the frontier — New model drops? You're testing it that day. New capability lands? You're the one who ships it
Move fast with AI tooling — Cursor, Claude Code, and whatever comes next; manage multiple coding sessions to compress weeks into days
Own the metric, not the feature — "We increased conversion by 15%," not "we shipped the thing"
Prove impact — Set up metrics, track results, present what worked to the company
You Might Be a Fit If...
You get energy from user and business impact, not code elegance
You write code with AI (Cursor, Claude Code, Windsurf) and can manage multiple coding sessions
You're full-stack by instinct—frontend, backend, and the AI layer that makes decisions
You've shipped AI to production—real systems serving real users, not demos
You ship fast and iterate—meaningful features in days that others take months on
You can present to non-technical people and explain why a metric moved
Requirements
Software engineering experience shipping production systems (level determined during interviews)
Proficiency in Python, TypeScript, or similar
Experience building and shipping AI-powered features—LLM applications, agent pipelines, or workflow automation
Ability to work across the stack: frontend, backend, and the AI layer
Based in San Francisco or willing to relocate
Nice to Have
Voice AI or real-time systems experience
RAG, agent frameworks, or evaluation systems
Background in operations tooling, sales tech, or workflow automation
Prior startup experience
Compensation & Logistics
Salary: $140,000–$280,000 depending on experience + performance bonuses & equity
Location: San Francisco, in-office. Based in SF or willing to relocate.
Schedule: Monday–Friday, very early morning start, in-office five days a week.
Benefits: Uber commuter benefits; breakfast, lunch, and dinner provided; snacks, drinks, and coffee daily; free gym membership; health, dental, and vision insurance.
The Process
Technical screen — 60 min remote: project deep dive + system design
Super Day on-site — meet the team, sit in on the operation, do real work alongside us.
To Apply
If you want to build AI capabilities against business problems you discover yourself, ship code that runs a real business, and work with people who show up with the same intensity every day—send your resume and a link to something you've built that had measurable business impact.