RAG

ML & AI Agentic AI & LLMs

Retrieval-augmented generation (RAG) is a technique that enables large language models (LLMs) to retrieve and incorporate new information from external data sources. With RAG, LLMs first refer to a specified set of documents, then respond to user queries. These documents supplement information from the LLM's pre-existing training data. This allows LLMs to use domain-specific and/or updated information that is not available in the training data. For example, this helps LLM-based chatbots access internal company data or generate responses based on authoritative sources.

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76 jobs · 57 companies · last seen 9 October 2026

There are currently 76 open roles in Berlin that mention RAG, posted by 57 companies. It frequently pairs with LLM, Python, Agentic AI. Seen most in genAI/LLM/Agentic AI (25% of their roles) and AI/ML (6% of their roles) and Product Manager (6% of their roles). Across those roles, 92% list it as required and 4% as nice-to-have.