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Clera

Founding Engineer

San Francisco$160k–$270kfulltimemidAdded today

About this role

Founding engineer role building a graph-native AI agent platform, owning core infrastructure including query engines, storage layers, and distributed systems. You'll make high-impact architecture decisions alongside the founding team in a small, infrastructure-focused startup.

What you'll do

  • Own and ship core infrastructure components spanning query execution, graph storage, and distributed systems
  • Make long-term architecture decisions with direct product impact alongside founders
  • Contribute to benchmark and research work that establishes the product category
  • Lead architecture reviews and navigate complex technical trade-offs with production consequences
  • Help scale the technical capabilities of the team as it grows
  • Design and implement production-grade systems under real load

What they're looking for

  • Rust or Go (required)
  • Distributed systems design and implementation
  • Query engine or storage layer architecture
  • Systems-level CS fundamentals and first-principles reasoning
  • Production infrastructure design
  • Large-scale system optimization
  • Architecture documentation and design patterns
  • Database or storage infrastructure experience (nice-to-have)

Benefits

  • Meaningful equity in founding-stage company
  • Learning budget
  • Flexible PTO
  • Wellness perks
  • High autonomy and architectural influence
  • On-site in San Francisco
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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 complex distributed system you designed—what trade-offs did you make and why?
  • Describe your experience building or optimizing a query engine or storage layer. What were the performance bottlenecks?
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