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Clera

Forward Deployed Engineer, DACH

San Francisco$80k–$150kfulltimemidAdded today

About this role

A Y Combinator-backed enterprise AI startup seeks a Forward Deployed Engineer to embed with major DACH customers and lead them through AI transformation. You'll design, build, and deploy production-grade agents and integrations while working directly with customer technical leaders and shaping the product roadmap.

What you'll do

  • Embed on-site with enterprise customers to scope, build, and deploy production agents and automated workflows end-to-end
  • Lead technical workshops, hackathons, and implementation sprints with customer CTOs and platform teams
  • Build custom integrations, MCP servers, and complex multi-step workflows tailored to customer needs
  • Identify platform limitations and collaborate with internal engineering to implement fixes and improvements
  • Train customers to independently own and operate systems post-deployment
  • Travel across the DACH region to support multiple key accounts

What they're looking for

  • Enterprise AI/LLM agentic systems and tool-use loops
  • Full-stack engineering with end-to-end solution delivery
  • Custom enterprise system integrations and MCP server development
  • Production-grade AI workflow architecture under load
  • Native German language proficiency
  • Go programming (preferred)
  • AI-assisted development tools (Claude Code, Cursor, etc.)
  • Stakeholder communication across technical and business contexts

Benefits

  • Early-stage equity opportunity at well-funded, high-growth startup
  • High-ownership role directly shaping product roadmap
  • Direct partnership with enterprise technical leaders
  • Opportunity to work on cutting-edge AI agent systems
  • Pragmatic, bias-toward-action work culture
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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 AI agentic system you shipped—what tool-use loops did it implement, and how did you ensure reliability under load?
  • Describe a time you embedded with an enterprise customer, scoped a complex use case in a live meeting, and delivered end-to-end. What went wrong and how did you handle it?
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