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Clera

Forward Deployed Research Engineer

San Francisco$150k–$250kfulltimemidAdded today

About this role

Join a small, high-caliber team building AI infrastructure to help frontier labs and data vendors train and evaluate models. As a Forward Deployed Research Engineer, you'll diagnose and resolve urgent technical challenges for key customers, transform firefighting into reusable tools, and operate independently in fast-moving situations.

What you'll do

  • Diagnose and resolve ambiguous technical problems across code, data, and environments for customers and partners
  • Own end-to-end technical deployment requests from triage through completion
  • Build tools and pipelines to solve urgent customer problems quickly
  • Clarify underspecified asks and identify what actually needs to be accomplished
  • Coordinate with research and go-to-market teams to unblock deployments
  • Convert recurring manual work into reusable tools and documented processes

What they're looking for

  • Python programming
  • Docker and containerization
  • Linux environments
  • Debugging across code, data, and complex systems
  • Reinforcement learning evaluation and benchmarking
  • Problem-solving in ambiguous situations
  • Technical communication with customers and cross-functional teams
  • Production incident management under pressure

Benefits

  • Salary: $150,000–$250,000 USD annually
  • Equity participation in early-stage, venture-backed company
  • Visa sponsorship available
  • Work on cutting-edge AI alignment challenges
  • Direct collaboration with frontier AI labs and data vendors
  • High-impact role with significant autonomy
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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.

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Likely interview questions

  • Walk us through a time you debugged a production issue across multiple systems (code, data, infrastructure). How did you approach it and what was the outcome?
  • Describe an ambiguous customer or partner request you received. How did you clarify what was actually needed and what trade-offs did you make between speed and quality?
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