Retrieval-Augmented Generation (RAG)

Frequently asked questions

• What is Retrieval-Augmented Generation (RAG) and how common is it in AI job postings?

  Retrieval-Augmented Generation (RAG) is a skill in the "LLM & Foundation Models" category. It currently appears in 439 active AI roles across 91 companies in our index.

• Which companies are hiring for Retrieval-Augmented Generation (RAG)?

  The top employers with active AI roles mentioning Retrieval-Augmented Generation (RAG) are: Amazon (44), Google (37), JPMorgan Chase (28), NVIDIA (19), Apple (18).

• Is demand for Retrieval-Augmented Generation (RAG) growing?

  Over the last 12 weeks, 316 new AI postings mentioned Retrieval-Augmented Generation (RAG). Demand is rising — up 200% in the last four weeks compared to the earliest four weeks in the window.

• At which stage of AI development is Retrieval-Augmented Generation (RAG) used?

  Roles requiring Retrieval-Augmented Generation (RAG) are concentrated in: agents (86%), application (5%), serving infrastructure (4%). These stages follow a seven-stage AI lifecycle from data preparation through to shipped product.

• What skills are commonly paired with Retrieval-Augmented Generation (RAG)?

  Job postings that mention Retrieval-Augmented Generation (RAG) most often also require: Large Language Models (LLMs), Agentic Systems, Python, Machine Learning, Generative AI.