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Clera

Software Engineer, AI & Data Systems

San Francisco$200k–$280kfulltimemidAdded today

About this role

Join a seed-stage people data and AI infrastructure company as a Software Engineer to build and operate a real-time identity graph platform. You'll own full-stack features spanning backend services, data pipelines, and AI agents, working directly with founders to ship products at scale.

What you'll do

  • Design and operate high-volume data pipelines and services with focus on reliability, security, and observability
  • Build AI agents, agent harnesses, and developer tooling then operate them reliably in production
  • Develop customer-facing products and platform capabilities across backend, data infrastructure, and frontend
  • Make architecture decisions, articulate tradeoffs, and iterate designs as requirements evolve
  • Translate customer requests into clear product decisions and working software alongside founders

What they're looking for

  • Backend engineering fundamentals (APIs, data modeling, distributed systems)
  • High-volume data pipeline design and operation
  • AI-native development with LLMs and agent frameworks
  • Production system ownership from concept through deployment and operations
  • Strong computer science fundamentals
  • Modern AI development tools and frameworks
  • Identity resolution or entity-matching systems experience
  • System architecture and design tradeoffs

Benefits

  • Competitive salary: $200,000–$280,000 USD annually
  • Early-stage startup with high ownership and impact
  • Work directly with founders and customers
  • On-site collaborative environment 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.

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Likely interview questions

  • Walk us through a production system you owned end-to-end—from initial concept through deployment and ongoing operations. What were the biggest challenges?
  • Describe your experience building and operating high-volume data pipelines. How did you ensure reliability and observability?
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