Adapt
Software Engineer
San Francisco$180k–$260kfulltimemidAdded 1 month ago
About this role
Adapt API is a venture-backed startup automating workflows in Property & Casualty insurance through an agentic operations platform. We're seeking experienced backend engineers to own end-to-end technical solutions and help shape the company's architecture from the ground up.
What you'll do
- Design and implement end-to-end workflows for the agentic platform in collaboration with customers
- Solve complex technical problems independently, managing the full development lifecycle
- Define and evolve the tech stack and system architecture based on requirements
- Work closely with the team to build and scale the core platform
- Contribute to team culture, internal tooling, and operational processes
What they're looking for
- Backend/full-stack engineering (4+ years)
- Systems design and architecture
- AI product development or data pipeline building
- API integration and third-party system connectivity
- TypeScript/JavaScript (preferred)
- Web scraping or browser automation (nice to have)
- Problem-solving in unstructured environments
- Clear code design and collaborative development
Benefits
- Above-market salary and equity
- Foundational role in rapidly-scaling post-PMF startup
- Challenging backend engineering problems
- Backing from top fintech investors and industry experts
- Full-time office position in San Francisco
Opens the application — the Jobs AI extension fills it for you. Set up autofill
Opens the official application on the employer’s site. No login required.
Adapt
Adapt API builds an agentic operations platform that automates workflows in Property & Casualty insurance. The company is hiring backend engineers to own technical solutions and help establish the company's foundational architecture.
View all jobs at AdaptLikely interview questions
- Tell us about a time you built an end-to-end workflow or integration from scratch. What were the hardest technical problems you solved?
- Describe your experience working with legacy systems, poorly documented APIs, or data extraction challenges. How did you approach integrating them?