Senior GenAI Engineer - Databricks (m/f/*) bei Ultra Tendency

As a Senior GenAI Engineer (m/f/*), you will lead the design and implementation of advanced data and AI solutions on the Databricks Lakehouse Platform. Your focus will lie in building robust ML pipelines, enabling GenAI capabilities, and delivering production-grade solutions that support data-driven innovation at scale. 

WHAT WE OFFER

• A chance to accelerate your career and work with outstanding colleagues in a supportive learning community split across 3 continents
• Contribute your ideas to our unique projects and make an impact by turning them into reality
• Balance your work and personal life through our workflow organization and decide yourself if you work at home, in the office, or on a hybrid setup
• Annual performance review, and regular feedback cycles, generating distinct value by connecting colleagues through networks rather than hierarchies
• Individual development plan, professional development opportunities
• Educational resources such as paid certifications, unlimited access to Udemy Business, etc.
• Local, virtual, and global team events, in which UT colleagues become acquainted with one another

• Design and implement GenAI solutions on the Databricks Lakehouse Platform, leveraging LLMs, embedding models, and vector search capabilities.
• Build and maintain RAG pipelines, including text preprocessing, embedding generation, and retrieval using vector databases.
• Work with Databricks’ Foundation Model APIs, MLflow, and other AI tooling to prototype and deploy GenAI applications.
• Collaborate with data engineers, ML engineers, and business stakeholders to build impactful GenAI use cases - (e.g., chatbots, document Q&A, code assist, summarization).
• Evaluate and fine-tune foundation models, manage prompt engineering, and optimize performance.
• Contribute to the development of GenAI best practices across model selection, security, governance, and cost-efficiency. 

WHAT YOU’LL BRING

• Hands-on experience with GenAI tools and frameworks, such as OpenAI, Hugging Face Transformers, LangChain, or similar.
• Experience building and deploying GenAI solutions in production or experimental environments.
• Familiarity with Databricks AI/GenAI stack (Foundation Model APIs, MLflow, Unity Catalog, Vector Search).
• Strong Python skills and good understanding of LLMs, tokenization, embedding models, and prompt engineering.
• Comfort working with unstructured data (text, documents, JSON) and modern GenAI architectures (RAG, LLMOps).
• Excellent collaboration and communication skills to work across AI, data, and product teams.
• Fluent German & English communication skills (written and spoken). 

Nice to have

• Experience implementing retrieval-augmented generation (RAG) pipelines using vector databases (e.g., FAISS, Chroma, Weaviate).
• Familiarity with Lakehouse AI, Unity Catalog for GenAI governance, and Databricks MosaicML.
• Background in NLP, question answering, summarization, or GenAI product development.