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 be one of the most senior engineers at Harper. That means you own systems end-to-end.

The Thesis

The difference between MTS and Senior MTS: you own outcomes, not tasks. You look at a business problem—“we need to 10x our quoting capacity”—and figure out what to build, build it, and make sure it works. You architect systems AND implement them. You mentor by building alongside people, not by reviewing PRs from a distance.

The Role

This isn’t a “tech lead who attends meetings” role. You make architectural decisions that stick, and ship code that directly generates revenue. No waiting for consensus—we don’t have time for consensus.

What You’ll Do

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

• Design agent architecture — Define abstractions that let us ship new agents in days

• Build evaluation that works — Systems that measure whether agents are getting better at closing deals

• Architect decision trace capture — Make every AI judgment traceable

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

You Might Be a Fit If…

• You’ve owned production systems (not contributed to—owned; you got paged when it broke)

• You architect AND implement—the best architecture comes from people who live with what they build

• You’ve built AI systems in production (LLM applications, agent frameworks, RAG, voice AI)

• You write code with AI (Cursor, Claude Code) and manage multiple sessions

• You’re 3-6 years into your career

Requirements

• 3-6 years software engineering experience

• Production experience with LLM applications and AI systems

• Strong architectural skills with hands-on implementation

• Track record of owning systems end-to-end

• Based in San Francisco or willing to relocate

Nice to Have

• Voice AI or real-time systems experience

• Experience building agent frameworks or evaluation systems

• Prior startup experience

Compensation

• Salary: $160,000–$230,000 + performance bonuses & equity

• Location: San Francisco, in-office

Benefits

• Health, dental, and vision insurance

• Commuter benefits

• Team meals and snacks

The Process

1. 15-min founder call — Alignment on mission and pace

2. If in SF: Super Day on-site

3. If outside SF: Technical phone screen, then on-site

To Apply

If you want to own systems that run a real business and work with founders who will actually listen to you—send your resume and tell us about a system you’ve owned.