Posted 2 months ago
Founding Engineer
AI Summary
Builds and scales AI agents and infrastructure for an insurance company, turning operational work into software and coordinating across carrier systems.
About this role
The opportunity
Hedge is hiring a founding engineer to build the agents that run an insurance company and the infrastructure that lets them scale. You’ll build systems that read messy submissions, chase missing information, navigate carrier requirements, and move accounts from a broker’s first email toward coverage.
Our agents are already in production, doing real work for paying customers. You’ll push them further: coordinating across carrier systems, recovering when things break, and improving through evals and feedback loops grounded in real outcomes.
You’ll build alongside the founders, inside the operation, with more than 100 insurance market partnerships already in place. The opportunity is to turn the work of placing insurance into software and give a small team the capacity to serve thousands of brokers.
How Hedge started
Luke Rosa and Luke Button worked together launching new markets at Traba, where Rosa built AI agents to manage $20 million in revenue. Buying insurance for Traba’s high-risk operations showed them how slow and manual the industry was.
Button later built Fernstone, an AI-native retail brokerage, and discovered a deeper bottleneck at the wholesale layer: access to carriers and control over the insurance product. They founded Hedge to address it, pairing Rosa’s experience automating operations with Button’s brokerage experience. Starting with wholesale distribution, Hedge is building toward an insurance company that combines distribution and underwriting.
What you will own
Turn operational work into software. Work alongside brokers and the founders, follow real submissions, and build systems around the details that determine whether an account gets quoted and placed.
Productionize and scale the platform. Own architecture, data models, background jobs, integrations, monitoring, and failure recovery. Take responsibility for what happens after a feature ships.
Put agents to work in production. Extend agents that handle emails, interpret submissions, gather missing information, prepare documents, and coordinate carrier workflows. Build evals and feedback loops that use real outcomes to improve performance, and own the reliability of the complete workflow.
Make messy carrier data usable. Turn PDFs, emails, and API responses into consistent records of coverage, pricing, and outstanding requirements. Catch mistakes before they reach a broker or customer.
Connect engineering to business results. Understand how your decisions affect turnaround, conversion, servicing effort, and carrier relationships.
Who thrives here
You’re deeply technical, resourceful, and willing to learn the business in detail. You can move from a conversation with a broker to debugging a production failure to making an architecture decision.
We look for:
Ownership from zero to one. You’ve taken an unclear problem to working software that people actually use. You can explain what you personally built, the decisions you made, and what happened after launch.
Technical depth. You can reason through data integrity, asynchronous workflows, reliability, and scaling. You know how to investigate a system when its behavior surprises you.
Exceptional work ethic and grit. When progress stalls, you investigate, find a way forward, and follow through. You’re willing to do the hands-on operational work required to understand and solve the problem.
Business judgment. You care whether the software helps people get work done and improves the economics of the business.
Speed and initiative. You identify useful work, build a first version, test it with real users, and improve it quickly.
There is no fixed years-of-experience requirement. The bar is high: show us technical depth, substantial ownership, and outsized initiative. Insurance experience is useful, but you can learn it here.
How we work
We work seven days a week, with six days together in our San Francisco office. This is a high-intensity environment with fast decisions and substantial individual responsibility.
We use AI heavily for both engineering and production. You’ll have access to the latest frontier models and are expected to use them aggressively. We build prototypes quickly, try different approaches, and use what we learn to decide where to invest. You remain responsible for understanding, testing, and operating what you ship.
Compensation and ownership
$150K–$250K base salary and 1%–3% equity, based on experience and scope. We offer health benefits and substantial responsibility for the company you’re helping build.
Skills
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