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Clera

Founding Engineer

San Francisco$160k–$270kfulltimemidAdded 3 days ago

About this role

Join a well-funded seed-stage startup as a Founding Engineer to build core infrastructure for a graph-native database designed for AI agents. You'll own major system components—query engines, storage layers, and distributed systems—while making architectural decisions that shape the product long-term alongside the founding team.

What you'll do

  • Design and ship query execution engines and graph storage layer components
  • Make high-impact architecture decisions with production consequences
  • Own large, ambiguous infrastructure problems end-to-end
  • Contribute to benchmark and research work defining the technical category
  • Participate in architecture reviews and navigate complex technical trade-offs
  • Help establish engineering practices as the team scales

What they're looking for

  • Rust or Go (proficiency required)
  • Distributed systems design and implementation
  • Query engine or storage layer architecture
  • Systems programming and first-principles thinking
  • Production systems ownership and shipping
  • Database or storage infrastructure (preferred)
  • Open source systems-level contributions (preferred)
  • Technical documentation and design

Benefits

  • Meaningful equity stake in well-funded startup
  • Competitive salary $160,000–$270,000 USD
  • Free daily meals and wellness programs
  • Top-tier hardware and software setup
  • Learning budget for books, courses, conferences, and personal projects
  • Flexible PTO and periodic team offsites
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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 distributed system component you shipped in production—what were the key trade-offs you made and why?
  • Describe your experience building or optimizing a query execution engine or storage layer. What challenges did you encounter?
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