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Clera

Founding Engineer ($3M pre-seed)

New York (Remote)fulltimemidAdded 1 month ago

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 Clera

Likely 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?