Senior Member of Technical Staff

Harper is an AI-native commercial insurance company in San Francisco. We're not bolting AI onto insurance — we're rebuilding the entire business as software, on a simple bet: turning expert human judgment into compute is one of the largest transitions left to make, and a trillion-dollar industry still run 90% by hand is the place to prove it. We've grown ~100x in the last year and we move at that speed — on-site, in person, long days, very high standards. Almost no one joins Harper for insurance; they join to build the company that replaces how it works.

The role

You'll be one of the most senior engineers at Harper, which here means one thing: you own outcomes, not tasks. Someone hands you a business problem — "we need to 10x our quoting capacity" — and you figure out what to build, build it, and make sure it works in production. The bet runs straight through the systems you'll own: the AI infrastructure that turns expert insurance judgment into compute. You architect and implement, because the best architecture comes from people who live with what they build. You mentor by building alongside people, not by reviewing PRs from a distance. This isn't a tech-lead-who-attends-meetings role — you make architectural calls that stick and ship code that directly generates revenue. We don't wait for consensus; we don't have time for it.

What you'll do

• Own the core AI infrastructure. LLM orchestration, prompt management, retrieval systems, structured output parsing.

• Design agent architecture. Define the abstractions that let the team ship new agents in days.

• Build evaluation that works. Systems that measure whether agents are actually getting better at closing deals — not whether the demo passed.

• Architect decision-trace capture. Make every AI judgment traceable, so the system can learn from its own history.

• Own platform scale. Thousands of concurrent conversations, sub-second response times.

What we're looking for

• 3+ years building software, with a track record of owning systems end-to-end — owned, not contributed to; you got paged when it broke.

• You architect and implement; you've built AI systems in production (LLM applications, agent frameworks, RAG, voice).

• You write code with AI (Cursor, Claude Code) and run multiple sessions at once.

• Strong architectural judgment paired with hands-on implementation.

• Bonus: voice or real-time systems; agent frameworks or evaluation systems; prior startup experience.

The reality

On-site in San Francisco, in person, long days, high standards. The trade for the intensity is rare: you make architectural decisions that stick, you ship without a consensus gauntlet, and founders will actually listen to you. That only works with senior people who want ownership over process. The right person reads the pace as the point.

Logistics

• Location: San Francisco, in-office. Based here or willing to relocate.

• Benefits: Uber commuter benefits; breakfast, lunch, and dinner provided; snacks and coffee stocked; free gym membership; health, dental, and vision.

• Process: 15-min founder call → Super Day on-site (technical phone screen first if you're outside SF).

To apply: Send your resume and tell us about a system you've owned end-to-end.