Clera
Founding Engineer ($3M pre-seed)
About this role
Join Clera as engineer #4 to build AI-powered recruiting automation that disrupts a $600B industry. You'll own entire product areas, ship daily to production, and work directly with experienced founders in a San Francisco hackerhouse environment.
What you'll do
- Own full product features from concept through deployment and iteration
- Build agentic AI systems that automate complex recruiting workflows
- Ship code to production daily and rapidly prototype new ideas
- Collaborate directly with CTO and founding engineering team on technical direction
- Engage with customers to gather feedback and refine product priorities
- Scale systems from initial launch to production reliability
What they're looking for
- TypeScript and React development
- AI-assisted coding with Cursor and similar tools
- LLM API integration and experience
- Full-stack web development
- Rapid prototyping and iteration
- Startup mentality with high agency and resourcefulness
- Customer-focused product thinking
- Systems that balance speed with scalability
Benefits
- Meaningful equity stake as early engineer
- Direct impact on product direction and company trajectory
- Living in SF hackerhouse with zero commute and tight feedback loops
- Competitive salary with significant equity upside
- Work alongside experienced founders and A-player team
- Visa sponsorship support available
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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
- Walk us through a project where you built something with TypeScript and React from scratch to production. How did you approach the architecture decisions?
- Tell us about your experience working with LLM APIs. What have you built, and how do you think about integrating AI into products effectively?