Clera
Founding Engineer
San Francisco$120k–$250kfulltimemidAdded today
About this role
Join a Y Combinator-backed enterprise AI startup as a Founding Engineer, operating at near-CTO level to build and scale an agentic operating system that automates complex workflows. You'll own large product areas end-to-end, working across Go backend and React/TypeScript frontend with direct user interaction and minimal oversight.
What you'll do
- Own product features end-to-end from discovery through production deployment
- Build and improve agentic AI systems focusing on accuracy, reliability, and capability expansion
- Work full-stack: Go backend services and React + Vite (TypeScript) frontend applications
- Engage directly with users to understand pain points and scope impactful features
- Design and implement AI-driven product features with real-world business impact
- Maintain high code quality standards through rapid, thoughtful code reviews
What they're looking for
- Go (Golang) — production backend experience (required)
- React and TypeScript — modern frontend development (required)
- REST and gRPC APIs in microservices architectures
- CI/CD, automated testing, deployment workflows, and production monitoring
- Agent orchestration, prompt engineering, and LLM frameworks (nice-to-have)
- Cloud platforms (AWS/GCP) and containerization (Docker/Kubernetes)
- Relational databases (Postgres/MySQL) and NoSQL systems
- Product thinking and ownership in ambiguous environments
Benefits
- Salary: $120,000–$250,000 USD annually
- Generous equity package at founding-engineer level
- Unlimited AI tooling budget for development
- Direct collaboration with technical co-founders
- Rapid career growth in high-ownership role
- On-site in San Francisco with genuine founding-stage autonomy
Likely interview questions
- Walk us through a Go backend service you built in production—what were the key architectural decisions and operational challenges?
- Tell us about a time you shipped a full-stack feature (backend + frontend) without clear specifications. How did you scope it and validate the approach?
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