Find leverage. Build solutions. Move revenue.

The Problem

36 million businesses in America need insurance. It’s not optional—regulations require it, contracts demand it, landlords won’t lease without it. Yet the industry is broken.

77% of small businesses are underinsured. 40% have no coverage at all. They’re running with risk because the distribution system failed them—too slow, too opaque, too confusing to navigate.

Over 90% of commercial insurance distribution is still human-led. We’re building the inverse: 90%+ AI-led, inching toward the higher 90s.

Somewhere in that transition, there’s leverage hiding everywhere—inefficiencies that the right engineer could eliminate with the right solution built in the right week.

The Thesis

Every industry with human-bounded distribution consolidates rapidly once someone makes it computational. When distribution becomes computational, Jevons Paradox kicks in: efficiency leads to expansion, not contraction.

But turning judgment into compute isn’t a one-time project. It’s a constant hunt for leverage. Where is the AI failing? Where are humans stuck? Where is one automation worth ten hires?

The AI landscape changes monthly. What was impossible in January is table stakes by June. New models drop, new capabilities emerge, new patterns become possible. Someone needs to be on the frontier—figuring out what’s newly possible and applying it before anyone else does.

That’s this role.

The Role

You’re a technical generalist who views engineering as a tool for solving business problems—not the end goal itself. You get energy from seeing revenue move, not from elegant abstractions.

At Palantir, FDEs embed with customers. At Harper, you’ll embed with our operations: sales, customer service, underwriting, carrier relations. You’ll see where things break. You’ll identify the 20% of problems that cause 80% of friction. Then you’ll build the solution.

This is not a research role. You prototype something Monday, ship it Tuesday, measure results Wednesday. If it works, you push to production. If it doesn’t, you try something else.

This is not a pure engineering role. You’ll present to the team on what you’ve learned. You’ll argue for priorities based on business impact. You’ll care about revenue, not just code quality.

We’re a growing engineering team looking for high-agency operators who can find and capture leverage.

What You’ll Do

Find leverage. Sit with the sales team and figure out why conversion is dropping. Dig into customer service and find the tickets that eat all the time. Talk to ops and discover the workflow that nobody’s automated because nobody knew it could be. Last week’s impossible is this week’s opportunity.

Build solutions fast. AI agents, automations, internal tools—whatever the problem demands. A voice agent that qualifies leads overnight. Document parsing that eliminates manual data entry. Custom workflows that turn five-hour processes into five-minute ones. You’ll prototype in days and ship in weeks.

Stay on the frontier. New model drops? You’re testing it that day. New capability unlocked? You’re figuring out how to apply it. You’ll be the person who knows what’s newly possible—and has the context to know where it matters most.

Prove impact. Did conversion go up? Did ticket time go down? Did the team stop doing that manual thing? You’ll set up the metrics, track the results, and show what worked.

Communicate what you learn. You’ll present to the company. You’ll shape the roadmap based on what you’ve seen on the ground. You’ll be the bridge between operations and engineering.

You Might Be a Fit If…

You get energy from business impact. Other engineers optimize for code elegance. You optimize for results. You’d rather build something ugly that moves revenue than something beautiful that ships “someday.”

You’re a technical generalist. Python, TypeScript, SQL—you can build a web app, set up an API, wire up an AI model. You learn new tools in days, not weeks.

You write code with AI. Cursor, Claude Code—you’ve figured out how to multiply your output. You can manage multiple coding sessions simultaneously.

You can present to non-technical people. You can explain to a sales lead why conversion dropped, what you built to fix it, and why it’s working.

You build fast. You’ve shipped meaningful work in under a week. You’re comfortable iterating in front of stakeholders, not just in private.

You think in business terms. Not “we shipped the feature” but “we increased conversion by 15%.”

You’re 2-5 years into your career. Enough experience to be autonomous. Not so much that you’ve forgotten what it feels like to build from scratch.

Compensation

Salary: $140,000 - $200,000

Equity: 0.05% - 0.25%

Location: San Francisco, in-office. We build together.

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

The Super Day: You’ll show how you rapidly gain context, translate business problems into technical solutions, and ship fast. We assess how you think about leverage, how you communicate impact, and how you build.

To Apply

We’re building a vertically integrated AI platform that connects go-to-market, sales operations, customer service, and retention under one architectural roof. That integration creates compounding through feedback loops—every interaction makes the system smarter. Thousands of businesses already trust us.

At Palantir, FDEs deploy existing software to customers. At Harper, you’re building new AI capabilities against business problems you discover yourself. The AI landscape changes monthly. What was impossible in January is table stakes by June. You’ll be on the frontier—figuring out what’s newly possible and applying it before anyone else does.

If that’s the kind of autonomy and impact you want—send your resume and tell us about something you built that had measurable business impact.

We’re a championship-minded team. We push each other. We move fast. We care about craft. If that sounds like where you belong, let’s talk.