Forward Deployment Engineer
New
C
CleraAI Phone Assistant
Candidates must be based in Germany.Full-TimeMiddle
Salary60,000 - 90,000 EUR per year
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Job Details
- Experience
- 3+ years
- Required Skills
- PythonSQLCloud ComputingTypeScriptPrompt Engineering
Requirements
- 3+ years of hands-on experience in deployment engineering, delivering production AI integrations and automation workflows.
- Deep experience with AI/LLM-based systems including prompt design, tool use, RAG, evaluation, and handling failure modes.
- Proven ability to translate complex business processes into robust, testable AI-driven workflows.
- Experience building integrations to third-party systems (APIs, webhooks, CRMs, calendars, ticketing, payments).
- Understanding of authentication patterns (OAuth, API keys) and data formats.
- Solid coding ability to implement glue code and features, including tests, monitoring, and logging.
- Cloud fundamentals, including deployments, observability, and production debugging.
- Pragmatic, delivery-focused mindset with an ability to ship and iterate quickly.
- Proficiency in TypeScript or Python preferred.
- Familiarity with n8n or similar workflow automation tools is a plus.
- Knowledge of voice/telephony integrations is a plus.
- SQL proficiency and experience with monitoring/tracing tools is a plus.
- GDPR / Privacy-by-Design awareness.
Responsibilities
- Act as the technical bridge between product and customer setups by translating requirements into production-ready implementations.
- Lead end-to-end rollouts of AI assistant configurations, including workflows, logic, data flows, prompts, and guardrails.
- Implement integrations with third-party systems via APIs and webhooks for CRM, calendar, ticketing, and payments.
- Develop glue code and features to map customer use cases to production systems with appropriate tests, monitoring, and logging.
- Debug live issues across calls, flows, and data pipelines to deploy rapid fixes under production conditions.
- Build reusable templates, deployment playbooks, and best practices to improve deployment scalability.
- Maintain a feedback loop with the product team by identifying feature gaps and recurring patterns.
- Own deployment success and ensure reliability of customer setups in live environments.
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