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Clera

Founding Engineer: Agent Infrastructure

San FranciscofulltimemidAdded 1 month ago

About this role

Join an early-stage startup as a Founding Engineer to design and build core agent infrastructure powering a people-data platform. You'll own projects end-to-end, architect production systems handling millions of requests, and directly shape the company's technical strategy alongside founding leadership.

What you'll do

  • Design and build core infrastructure for APIs, LLM workflows, scraping systems, and knowledge graphs
  • Architect production-grade systems handling millions of API requests with focus on performance and reliability
  • Own projects from problem definition through deployment and iteration
  • Collaborate with founding leadership on technical decisions and roadmap priorities
  • Contribute across the stack including documentation, tutorials, and internal tooling
  • Build experimental systems to stress-test and showcase platform capabilities

What they're looking for

  • Production systems architecture and design
  • Cloud and Linux server environments
  • API design and development
  • LLM-powered systems or AI workflows
  • Large-scale data systems or knowledge graphs
  • System reliability and performance optimization
  • Full-stack development capabilities
  • First-principles problem-solving
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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 production system you shipped end-to-end. What were the biggest technical decisions, and how did you handle tradeoffs between speed and reliability?
  • Describe your experience designing APIs or infrastructure to handle scale. What performance bottlenecks have you encountered, and how did you optimize for cost and latency?
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