Forward Deployed Operations

Harper•San Francisco, CA

6d•$125,000 - $175,000•Onsite

About The Position

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. A trillion-dollar industry runs on knowledge nobody wrote down — what the data means, what the operation actually needs, what users are motivated by, and where the leverage hides. This role synthesizes those disconnected streams into one thing: a clear read on the most important problem to solve next. Then you build the thing that solves it. You'll embed with the operators who run Harper — sales, service, underwriting, carrier relations — learn the operation end-to-end, find the 20% of friction causing 80% of the drag, and ship the thing that removes it. One day you're chasing a stalled quote with an underwriter. The next you're shipping the automation that makes sure no quote stalls again. The day after, you're on a customer call, feeding what you heard into a product spec. You run the operation and you improve the operation — both, always. It takes a curious, analytical mind, sharp product intuition, and genuine empathy for the people doing the work. This is on-site in San Francisco, in person, long days, high standards. A real share of the week is follow-ups, chasing, coordination, and cleanup — the operational backbone, done well. The system-building is earned by doing the unglamorous work first. Ambiguity is the job, not a phase. Scope shifts week to week. If you need a fixed lane and a clean spec, you'll be uncomfortable here. The ceiling is high and real. People who are exceptional here go on to run functions, lead teams, or start companies — because they've seen how the whole business works. That's the payoff, and it's on the other side of the grind.

Requirements

Shipped internal tools or automations end-to-end — not just designed them.
Run real operations: customer-facing, process-heavy, or both. You know what it feels like when a system breaks at 7 AM.
Measure yourself in business outcomes: "conversion went up 15%," not "the feature shipped."
Can walk into a room of non-technical operators, explain why a number moved, and have them trust you.
Would rather own a messy problem end-to-end than execute a clean task someone handed you.
Been exceptional at something before, and you're looking for the place that finally matches your ceiling.
2–4 years in a high-pace environment (startup, operations, consulting, or engineering);
A track record of building and shipping things that ran in production — internal tools, automations, workflows;
Comfortable in SQL and at least one of Python or TypeScript;
Hands-on with AI coding tools (Cursor, Claude Code, or equivalent), not just aware of them;
Strong written and verbal communication with both technical and non-technical audiences;
Based in San Francisco or willing to relocate immediately.

Nice To Haves

LLMs, AI agents, or voice AI experience;
A background in insurance, fintech, or another regulated, high-stakes industry;
Prior startup or founder experience;
Solutions engineering, operations, or customer success experience.

Responsibilities

Find the leverage. Sit with operators, watch the work, and surface the automations nobody built because nobody knew they were possible yet.
Run the operation. Underwriter follow-ups, carrier communications, customer calls, keeping deals moving through the pipeline. You're in the work, not above it.
Build fast. AI agents, internal tools, workflow automations — prototype in days, ship in weeks.
Instrument everything. Write SQL, pull the data, build the dashboard. Prove what you shipped moved a number — in business terms, not feature terms.
Shape what gets built next. Translate operational pain into product requirements. The patterns you spot become the things engineering builds next.
Move where it's urgent. Context-switch across functions based on what matters most this week. Scope doesn't respect org charts here.