AI Engineer - FDE (Forward Deployed Engineer)

<p><strong>AI Engineer - FDE (Forward Deployed Engineer)</strong></p> <p><strong>Req ID: CSQ427R332</strong></p> <p><strong>We welcome remote applicants located near our offices. Preferred locations: Munich, Germany.&nbsp;Remote location for candidates to be based in the Germany region only (not remote from any other country)</strong></p> <p><strong>Mission</strong></p> <p>The AI Forward Deployed Engineering (AI FDE) team is a highly specialised customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specialisations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly.</p> <p>Reporting to: Senior Manager - AI FDE, EMEA</p> <p><strong>The impact you will have:</strong></p> <ul> <li>Develop cutting-edge GenAI solutions, incorporating the latest techniques from <a href="https://www.databricks.com/blog/category/databricks-ai?categories=databricks-ai%2Cai-research%2Cai-engineering">Databricks AI research</a> to solve customer problems</li> <li>Own production rollouts of consumer and internally facing GenAI applications</li> <li>Serve as a trusted technical advisor to customers across a variety of domains</li> <li>Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally</li> <li>Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap&nbsp;</li> </ul> <p><strong>What we look for:</strong></p> <ul> <li>Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy</li> <li>Expertise in deploying production-grade GenAI applications, including evaluation and optimisations&nbsp;</li> <li>Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.</li> <li>Experience building production-grade machine learning deployments on AWS, Azure, or GCP</li> <li>Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent pract