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Clera

Founding Engineer

remote (Remote)$88.6k–$155kfulltimemidAdded today

About this role

Join a freshly funded startup as the first engineering hire, taking their AI agent product from working prototype to scalable infrastructure supporting millions of users. You'll work directly with the founder to build the core runtime and technical foundation, with a clear path to CTO as the team grows.

What you'll do

  • Transform prototype into production-grade agentic infrastructure capable of handling a million users
  • Design and own the agent runtime including orchestration, memory management, and verification systems
  • Make end-to-end technical decisions across backend, infrastructure, frontend, and agent systems
  • Establish technical standards, architecture patterns, and engineering practices from the ground up
  • Ship weekly updates to real businesses actively using the platform
  • Define the technical stack and build processes for the early team

What they're looking for

  • Production software deployment and scaling (2+ years or equivalent)
  • LLM and AI agent systems in production environments
  • Full-stack development across backend, infrastructure, and frontend
  • System architecture and data modeling for high-scale applications
  • Agent orchestration and multi-agent workflows
  • Technical leadership and decision-making without organizational hierarchy
  • Rapid prototyping and iterative shipping cadence
  • CS fundamentals and strong engineering practices

Benefits

  • Path to CTO role as company scales
  • Relocation support and US visa sponsorship
  • Opportunity to shape technical direction from day one
  • Work directly with founder in early-stage environment
  • Fully remote initially within Europe
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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 took an AI or ML system from prototype to production—what were the biggest scaling challenges and how did you solve them?
  • Describe your experience designing agent orchestration or runtime systems—how did you approach memory, state management, and reliability?
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