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Clera

Software Engineer

San Francisco$130k–$220kfulltimemidAdded today

About this role

Full-stack software engineer needed to design and build an AI agent platform serving the hospitality industry. You'll own the end-to-end system handling guest communication and operations at scale, from response pipelines and knowledge retrieval to tool orchestration and observability.

What you'll do

  • Design response generation pipelines including routers, orchestrators, and synthesizers for intent classification and tool selection
  • Develop knowledge retrieval systems that ground agent responses in accurate customer data
  • Build tool orchestration layers that execute multi-step workflows with graceful failure handling
  • Create evaluation frameworks measuring quality against real conversations to catch regressions
  • Implement observability and tracing that makes agent reasoning transparent to support teams
  • Extend platform to voice conversations with real-time transcription and tool-use capabilities

What they're looking for

  • Production AI/ML systems design and debugging
  • Retrieval systems and semantic search
  • Multi-step workflow and function-calling orchestration
  • Backend development (Python, Go, Rust, or Java)
  • Observability, tracing, and debugging tooling
  • Third-party API integration and failure handling
  • Model routing and prompt optimization
  • Full-stack development across infrastructure and data pipelines

Benefits

  • Equity stake (0.20% to 1.20%)
  • Comprehensive health insurance
  • 401(k) match
  • Relocation support available
  • Meaningful product ownership and autonomy over architecture decisions
  • Small, flat team environment
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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

  • Tell us about a time you shipped a production AI/ML system—what went wrong and how did you debug it?
  • How have you approached building and evaluating retrieval systems in the past, and how did you measure their effectiveness?