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Clera

Founding Engineer

New York (Remote)$180k–$250kfulltimemidAdded today

About this role

Join a founding engineering team building multi-modal AI agents for sports tech and sales automation. You'll own an entire domain end-to-end—from architecture to production—make product decisions directly with customers, and ship features across voice, SMS, and email channels.

What you'll do

  • Own one of four core engineering domains end-to-end, including architecture, feature development, and production operations
  • Participate in customer calls, gather feedback, and drive independent product decisions without a PM layer
  • Build and optimize multi-modal agents targeting sub-500ms voice latency and robust conversation state across channels
  • Define quality standards for non-deterministic systems through evals, prompt versioning, guardrails, and drift detection
  • Work full-stack across React/Next.js frontends, Node.js backends, and Python voice services
  • Ship features and manage daily production deployments in a fast-moving startup environment

What they're looking for

  • TypeScript and Node.js (hard requirement)
  • React/Next.js frontend development
  • LLM APIs and agent SDKs (Anthropic, OpenAI, Vercel AI SDK, or Mastra)
  • Production voice or SMS agents
  • Long-running agent state and memory management
  • Agent evaluation and guardrails
  • Python for real-time voice pipelines (LiveKit, Deepgram, STT/TTS)
  • Full-stack system design and 0-to-1 product development

Benefits

  • Equity compensation
  • Founding-stage role with high ownership and autonomy
  • Direct customer interaction and product influence
  • Work on cutting-edge multi-modal AI agents
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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

  • Tell us about a 0-to-1 product you shipped at a startup or new team. What was your role, and how did you balance shipping speed with quality?
  • Walk us through a production LLM or agent application you built. What did evaluation and prompt management look like, and how did you handle drift?
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