Internship in GenAI Knowledge Assistant for Engineering

During your assignment, you will collect, structure and preprocess engineering knowledge sources such as technical documents, specifications, test reports and structured datasets.
You will evaluate suitable Databricks-native and open-source tools (e.g. RAG, Text-to-SQL, AI Agents, Vector Search, Genie) for different types of engineering content.
Based on this, you will design and implement natural language workflows on Databricks that allow hardware engineers to query both documents and structured data.
To deliver reliable, source-grounded answers, you will apply prompt and context engineering and ensure result quality and traceability (e.g. citations, evaluation, guardrails).
Additionally, you will collaborate closely with hardware engineers to understand use cases and iteratively improve the solution.
Finally, you will communicate progress and findings through visualizations, short presentations and technical documentation.
Education: master studies in the field of Data Science, Artificial Intelligence, Computer Science, Information Systems, Engineering or a comparable quantitative or technical area with good grades
Experience and Knowledge:
practical knowledge of large language models and Generative AI concepts such as RAG, embeddings, vector databases, prompt and context engineering, or AI agents
solid programming skills, ideally in Python and SQL
engineering background as a plus
experience with Databricks (e.g. Vector Search, Genie, Mosaic AI Agent Framework, MLflow), LangChain, LlamaIndex or other Generative AI frameworks as an advantage
understanding of heat pump technology and operating principles as an asset
Personality and Working Practice: you are curious and self-driven, bringing a structured approach and strong communication skills to engaging with engineers from different backgrounds, understanding their needs and translating them into technical solutions
Work Routine: we offer you the opportunity to work in a hybrid setup with regular on-site presence
Enthusiasm: passionate about bridging AI and hardware engineering and making complex technical knowledge easily accessible through natural language
Languages: very good in English

Employment type
Full-time

Work arrangement
Hybrid