Forward Deployed Engineer, FDE (L4)
Build and productionize customer data and AI solutions on Databricks, owning architecture and end-to-end delivery while guiding enterprise teams and shaping reusable assets and product feedback.
Join a small, fast moving engineering team at an AI communications software company. You will lead customer deployments from requirements through production, helping ensure voice AI systems work reliably and turning deployment insights into product improvements.
Translate customer requirements into robust implementation plans and production workflows.
Configure AI logic, prompts, data flows, and guardrails for live customer deployments.
Build integrations with third party systems using APIs, webhooks, OAuth, and API keys.
Develop and test glue code and features, with appropriate monitoring and logging.
Debug production issues across calls, workflows, and data, and deliver timely fixes.
Create reusable deployment templates and playbooks, and share recurring customer needs with product and engineering.
Several years of practical experience translating customer requirements into production implementations.
Hands on production experience with LLM applications, including prompting, tool use, retrieval augmented generation, evaluation, and failure analysis.
Strong coding skills for integrations and application features, plus experience with testing, monitoring, logging, and production debugging.
Cloud deployment and observability fundamentals, and a pragmatic, delivery focused approach.
German proficiency at B2 level or above. Exceptional candidates who do not meet this language level may also be considered.
Experience in a startup engineering environment is useful. Voice or telephony integrations, TypeScript or Python, SQL, automation tools, and privacy considerations are advantageous.
Base salary is €60,000 to €90,000 annually. Visa sponsorship is not available.
Remote, based in Germany.
Build and productionize customer data and AI solutions on Databricks, owning architecture and end-to-end delivery while guiding enterprise teams and shaping reusable assets and product feedback.
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