Retrieval-Augmented Generation: grounding LLM responses by retrieving relevant documents from a vector store or search index before generation, so answers cite real sources instead of hallucinating.
Primary AI lifecycle stage: agents and application.
As of today, 2,073 active AI roles across 201 companies in our index reference RAG. Hiring concentrates at the agents (85%) and application (4%) stages. Most common sectors: Enterprise, Big Tech, Banking.
Retrieval-Augmented Generation: grounding LLM responses by retrieving relevant documents from a vector store or search index before generation, so answers cite real sources instead of hallucinating. Primary AI lifecycle stage: agents and application.
2,073 active AI roles across 201 companies in our index reference RAG as of today.
The companies with the most active RAG listings are: Amazon (170 roles), JPMorgan Chase (150 roles), Adobe (78 roles), Google (78 roles), Capital One (69 roles).
RAG primarily belongs to the agents and application stages of the AI lifecycle. In current hiring, RAG roles concentrate at: agents (85%), application (4%).
The sectors with the most active RAG hiring are: Enterprise, Big Tech, Banking.
3483 AI roles tagged rag.
| Company | Title | Sector | AI score | Other tags |
|---|---|---|---|---|
| Databricks | Staff Machine Learning Engineer | Data AI | 8 | Fine-tuning · Model serving · Evals |
| Celonis | Senior Applied Value Engineering Consultant - Public Sector | Data AI | 8 | Agent orchestration · Tool use · Guardrails · LLM observability · Multimodal |
| DocuSign | Senior Machine Learning Engineer | Enterprise | 8 | Agent orchestration · Agent research · RL post-training · LLM observability · Vector DB · Fine-tuning · Inference infra · Model serving |
| Snowflake | Principal Machine Learning Engineer- Search Quality | Data AI | 8 | Search & ranking · Recommender systems · Vector DB · Agent orchestration · Tool use · Evals · LLM observability · Inference infra · Model serving |
| Microsoft | Member of Technical Staff - Principal Platform Engineer, Copilot Memory and Personalization | Big Tech | 8 | Vector DB · Search & ranking · LLM observability |
| Datadog | Staff AI Engineer - Notebooks | Enterprise | 8 | Agent orchestration · Tool use · Evals · Guardrails · Fine-tuning · Model serving |
| Datadog | Staff AI Engineer - Notebooks | Enterprise | 8 | Agent orchestration · Tool use · Guardrails · Evals · Fine-tuning · Model serving · Inference infra |
| Rubrik | Data Science Researcher (Part-Time 25%) | Enterprise | 8 | Fine-tuning · Agent orchestration · Vector DB |
| NVIDIA | Architect, AI Solutions Engineering | Semiconductors | 8 | Agent orchestration · Fine-tuning · Model serving · Inference infra |
| Autodesk | Software Architect | Enterprise | 8 | Agent orchestration · Agent research · Tool use · Inference infra · Model serving · Vector DB · LLM observability · Guardrails |
| Walmart | Distinguished, Data Scientist | Retail | 8 | Search & ranking · Recommender systems · Agent orchestration · Tool use · LLM observability · Model serving · Inference infra |
| Cresta | Senior Forward Deployed Engineer (AI Agent) - UK | Vertical AI | 8 | Agent orchestration · Tool use · LLM observability · Model serving |
| Weights & Biases | AI Solutions Engineer, Pre-Sales- W&B | Data AI | 8 | Agent orchestration · Tool use · Evals · Guardrails · Vector DB · Fine-tuning · Inference infra · Model serving · LLM observability |
| GEICO | Sr Staff Engineer - Applied AI | Insurance | 8 | Agent orchestration · Agent research · Vector DB · Model serving · Inference infra · Guardrails · LLM observability |
| Capital One | Applied Researcher I (Multi-agent Systems, Knowledge Graphs/GraphRAG/Graph-of-Thought / GoT, MCP, LangGraph, Agent Protocols) | Banking | 8 | Agent orchestration · Agent research |
| GEICO | Sr Staff Engineer - Applied AI | Insurance | 8 | Agent orchestration · Agent research · Vector DB · Model serving · Inference infra · Guardrails · LLM observability |
| Workday | LLM Engineer | Enterprise | 8 | Agent orchestration · Evals · LLM observability |
| Datadog | Manager I, Engineering - Applied AI - Natural Language & Conversational Interfaces | Enterprise | 8 | Agent orchestration · Semantic search · LLM observability · Evals |
| Oura | Staff Product Manager - Member Understanding & Intelligence | Consumer | 8 | LLM observability · Model serving · Recommender systems |
| Glean | Forward Deployed Product Manager | Enterprise | 8 | Agent orchestration · Vector DB |
| Datadog | Senior AI Engineer - Bits AI Security Analyst | Enterprise | 8 | Agent orchestration · Tool use · Guardrails · LLM observability · Model serving |
| Disney | Lead Machine Learning Engineer, Ad Platforms | Media | 8 | Recommender systems · Search & ranking · Fine-tuning · LLM observability · Multimodal · Vision · Evals |
| Writer | Software engineer, generative AI | AI Frontier | 8 | Agent orchestration · Tool use · Vector DB · Model serving · Inference infra |
| Writer | Software engineer, generative AI (UK) | AI Frontier | 8 | Agent orchestration · Vector DB |
| Uber | Security Engineer (AI & Agentic Systems) | Consumer | 8 | Agent orchestration · Evals · Guardrails · LLM observability · Agent research |
| Amazon | Applied Scientist II - Gen AI & LLM, PXT | Big Tech | 8 | Fine-tuning · Model serving · Evals · Agent orchestration |
| NVIDIA | Senior AI Infrastructure Software Engineer | Semiconductors | 8 | Agent orchestration · Inference infra · Model serving · Vector DB · Fine-tuning |
| Microsoft | Principal Applied Scientist | Big Tech | 8 | Code gen · Evals · Fine-tuning · Model serving |
| JPMorgan Chase | Agentic Development - Vice President | Banking | 8 | Agent orchestration · Agent research · LLM observability · Inference infra · Model serving · Tool use |
| JPMorgan Chase | Agentic Development Associate | Banking | 8 | Agent orchestration · Agent research · LLM observability · Tool use |