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Clera

Founding Engineer

New York (Remote)$170k–$220kfulltimemidAdded today

About this role

Join an early-stage data infrastructure startup as a founding engineer working directly with the CTO to build autonomous agents and distributed systems for large-scale web data extraction and analysis. You'll own significant product areas and work across the full stack to serve enterprise customers processing millions of data rows daily.

What you'll do

  • Build autonomous agents for complex information extraction across diverse web environments
  • Design and iterate on full-stack, self-serve applications for non-technical users
  • Maintain and scale backend architecture handling thousands of requests per second
  • Develop and manage ML pipelines and LLM-based agentic systems
  • Implement infrastructure as code and deployment automation
  • Contribute across the entire tech stack to maintain rapid iteration cycles

What they're looking for

  • LLM applications and agentic systems (RAG, model evaluation, fine-tuning)
  • Distributed backend systems design and optimization
  • Full-stack development (backend, frontend, infrastructure)
  • Infrastructure as code and deployment automation
  • Web scraping, data extraction, and browser automation at scale
  • Antibot systems and reverse engineering (preferred)
  • JavaScript deobfuscation and web automation (preferred)
  • Production software shipping in early-stage, 0→1 environments

Benefits

  • Significant ownership of core product areas
  • Direct collaboration with CTO
  • Visa sponsorship available
  • Early-stage equity opportunity (implied)
  • Fast-paced, collaborative environment
  • Full-stack learning and impact
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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

  • Tell us about a time you built and shipped a production LLM or agentic system—what were the key technical challenges?
  • Describe your experience designing distributed backend systems. How have you approached scaling to handle high request volumes?
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