Harper
Forward Deployed Engineer
New
140000 –200000 USD / yearUSASenioraimachine learningpython
Build AI-driven solutions to optimize commercial insurance operations by embedding with business teams and rapidly prototyping and delivering impactful improvements.
Responsibilities
- You’re a technical generalist who views engineering as a tool for solving business problems—not the end goal itself. You embed with operations: sales, customer service, underwriting, carrier relations. You see where things break. You identify the 20% of problems that cause 80% of friction. Then you build the solution.
- Prototype Monday, ship Tuesday, measure Wednesday. If it works, push to production. If not, try something else.
Requirements
- 2-5 years software engineering experience
- Proficiency in Python, TypeScript, or similar
- Experience building and shipping internal tools or automations
- Ability to work autonomously and move fast
- Based in San Francisco or willing to relocate
Nice to have
- Experience with LLMs, AI agents, or voice AI
- Background in operations, sales tech, or workflow automation
- Prior startup experience
Conditions
- Salary: $140,000–$200,000 + performance bonuses & equity
- Location: San Francisco, in-office
- Health, dental, and vision insurance
- Commuter benefits
- Team meals and snacks
Other
- 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.
- Somewhere in that transition, there’s leverage hiding everywhere—inefficiencies the right engineer could eliminate with the right solution built in the right week.
- 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. That’s this role.
- Find leverage — Sit with teams, discover what nobody’s automated because nobody knew it could be
- Build solutions fast — AI agents, automations, internal tools—prototype in days, ship in weeks
- Stay on the frontier — New model drops? You’re testing it that day
- Prove impact — Set up metrics, track results, show what worked
- Communicate what you learn — Present to the company; shape the roadmap
- You get energy from business impact, not code elegance
- You’re a technical generalist (Python, TypeScript, SQL—you learn new tools in days)
- You write code with AI (Cursor, Claude Code) and can manage multiple coding sessions
- You can present to non-technical people and explain why conversion dropped
- You think in business terms: “we increased conversion by 15%,” not “we shipped the feature”
- You’re 2-5 years into your career
- 15-min founder call — Alignment on mission and pace
- If in SF: Super Day on-site
- If outside SF: Technical phone screen, then on-site
- If you want autonomy, impact, and the chance to build AI capabilities against business problems you discover yourself—send your resume and tell us about something you built that had measurable business impact.