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Clera

AI Engineer (Mid-Level)

San Francisco$180k–$400kfulltimemidAdded today

About this role

Mid-level AI Engineer role at a pre-seed startup building agentic systems for enterprise automation across regulated industries. You'll own the full stack from LLM service design through production deployment, focusing on RAG pipelines, multi-agent orchestration, and reliability infrastructure for healthcare, legal, fintech, and compliance use cases.

What you'll do

  • Design and maintain agentic systems automating multi-step workflows in regulated domains
  • Build and operate production RAG pipelines with vector databases and retrieval infrastructure at scale
  • Implement multi-agent orchestration, tool-calling, memory, and reasoning components
  • Develop evaluation and safety infrastructure to measure performance and enforce reliability standards
  • Ship full-stack AI products from MVP to enterprise-grade with APIs, backend/frontend, and production operations
  • Collaborate with founders, product, and design to define metrics and iterate on user feedback

What they're looking for

  • Python and TypeScript/React development
  • Production LLM deployment and prompt engineering
  • RAG patterns, vector databases, and embeddings
  • Agent frameworks (LangGraph, CrewAI) and orchestration tools (Temporal, Trigger.dev)
  • AWS or GCP cloud platforms
  • Relational and NoSQL databases
  • Testing, evaluation, and monitoring for AI systems
  • API design and multi-tenant system architecture

Benefits

  • Salary range $180,000 to $400,000 USD annually including equity
  • Work on cutting-edge agentic AI systems at a pre-seed startup
  • Full-stack ownership of end-to-end features
  • Collaborate directly with founders and cross-functional team
  • On-site position in San Francisco with relocation support
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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 LLM system you've deployed—how did you handle prompt design, failure modes, and monitoring in production?
  • Describe your experience building or maintaining RAG pipelines. What trade-offs have you made between retrieval quality and latency?
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