About Fernstone:
Fernstone is building a new kind of insurance company: we combine AI with expert advisors to place insurance faster and at better terms.
We think AI will fundamentally reshape how insurance is bought and sold – and the new winners in this $1T category will compete directly with legacy insurers instead of selling software to them.
We’ve raised $3M from Y Combinator and other notable investors, and have grown from 0 to 500+ customers since launching at the start of the year.
Fernstone was founded by James http://bookface.ycombinator.com/user/737672/linkedin_redirect?key=f4f026c4cd7e51d1014e2de378f0e60f559cb6ac (BCG, Traba, UChicago), and Bryant https://www.linkedin.com/in/bryant-le-3884a7134/ (Google, SentiLink, Vanderbilt). We work in-person in our NYC office.
The role:
As founding engineer (and engineering hire #2), you’ll have a substantial role in building our product. You’ll work directly with the operators using your product, own critical systems across the stack, and help set the technical direction of the company. Your work will have a direct impact on how we operate, serve customers, and grow.
What you’ll work on:
- Own outcomes: partner with our operations team to learn how insurance work gets done, identify the biggest opportunities, and decide what to build.
- Build across the stack: Design and build complete features across the interface, application logic, data model, and infrastructure.
- Engineer for the real world: Create reliable workflows where accuracy matters, outside systems fail, and events may unfold over days or weeks
- Develop practical AI: Build systems that interpret information, automate multi-step work, and recognize when a person needs to step in.
What we look for:
- 2+ YOE
- You’ve shipped and maintained production software that people depend on.
- You can take an ambiguous business problem, ask good questions, and turn it into a focused solution.
- You have strong backend and relational database fundamentals, and you’re comfortable building a polished frontend.
- You think carefully about data correctness, failure handling, and how systems behave after deployment.
- You have practical experience building with language models, including evaluating their output and handling mistakes.
- You use AI development tools effectively and take responsibility for understanding, reviewing, and debugging the code you ship.