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Clera

Forward Deployment Engineer

remote (Remote)$60k–$90kfulltimemidAdded today

About this role

Bridge technical and customer needs as a Forward Deployment Engineer for an AI voice platform, owning end-to-end production rollouts, integrations, and real-world troubleshooting while feeding learnings back into product development.

What you'll do

  • Own production rollouts of AI workflows, prompts, guardrails, and data flows from requirements to live deployment
  • Implement third-party integrations via APIs, webhooks, and common services (CRM, calendar, ticketing, payments)
  • Develop glue code and small-to-medium features with testing, monitoring, and logging
  • Debug and rapidly resolve production issues across calls, workflows, and data pipelines
  • Create reusable deployment templates, playbooks, and best practices to scale customer setups
  • Identify and escalate product gaps and recurring pain points with concrete recommendations

What they're looking for

  • LLM systems (prompting, tool use, RAG, evaluation, failure modes)
  • API and webhook integration design including OAuth and API key authentication
  • Python or TypeScript for feature development and glue code
  • Cloud deployment and observability for production debugging
  • AI workflow design from complex business processes
  • Production deployment and incident response
  • Voice/telephony integrations (bonus)
  • Automation platforms like n8n (bonus)

Benefits

  • Fully remote position based in Germany
  • Competitive salary €60,000–€90,000 annually
  • Fast-moving AI environment with high-velocity product iteration
  • Direct impact on product roadmap through customer insights
  • Technical leadership at the product-customer intersection
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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 complex LLM-based workflow you deployed—what were the key failure modes and how did you handle them?
  • Describe your experience integrating third-party systems via APIs. How do you handle authentication and error scenarios?
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