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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54 jobs · 37 companies · last seen 21 May 2026

There are currently 54 open roles in Berlin that mention RAG, posted by 37 companies. It frequently pairs with LLM, Python, Agentic AI. Seen most in AI/ML (21% of their roles) and Leadership (9% of their roles) and Data Scientist (9% of their roles).