Clera
Backend Engineer
San FranciscoFrom $72kfulltimemidAdded today
About this role
Join an AI-native insurtech startup to build backend systems for an intelligent insurance platform. You'll own features end-to-end using TypeScript/Node.js, PostgreSQL, and Temporal workflows, working in a fast-paced remote environment where AI coding tools are part of daily development.
What you'll do
- Build and ship backend features including campaign engines, integrations, and core APIs
- Design multi-tenant PostgreSQL schemas with focus on migrations and query performance
- Implement event-driven workflows using Temporal for workflow orchestration
- Own features end-to-end from design through production deployment and support
- Collaborate with Head of Engineering on architecture decisions and code reviews
- Contribute to AI-native development practices using Claude Code and similar tools
What they're looking for
- TypeScript / Node.js
- PostgreSQL (multi-tenant design, migrations, optimization)
- Event-driven and queue-based architecture
- Temporal workflow orchestration
- AI coding assistants (Claude Code, Codex)
- CI/CD pipelines and automated testing
- AWS infrastructure and monitoring tools
- Production support and on-call readiness
Benefits
- Fully remote with international distributed team
- Early-stage equity opportunity
- Competitive salary up to $72,000 USD annually
- Opportunity to work with cutting-edge AI and LLM systems
- Fast-shipping, modern tech stack
Opens the official application on the employer’s site. No login required.
Clera
Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.
View all jobs at CleraLikely interview questions
- Tell us about a time you owned a feature end-to-end in production—what was the most challenging part?
- How would you design a multi-tenant PostgreSQL schema to ensure data isolation and query performance at scale?