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.
3483 AI roles tagged rag.
| Company | Title | Sector | AI score | Other tags |
|---|---|---|---|---|
| Amazon | Applied Scientist, Support Products & Services | Big Tech | 8 | LLM observability · Fine-tuning · Model serving |
| Databricks | AI Engineer - FDE (Forward Deployed Engineer) - U.S. Federal Sector | Data AI | 8 | Agent orchestration · Fine-tuning · Model serving · Evals |
| Microsoft | Research Intern - AI Safety & Reliability for LLM Systems | Big Tech | 8 | Agent orchestration · LLM observability · Guardrails · Evals |
| Clay | Product Manager, Enrichment & AI | Vertical AI | 8 | Agent orchestration |
| Microsoft | Applied Researcher 2/ Senior Applied Researcher | Big Tech | 8 | Fine-tuning · Agent research · Code gen · LLM observability · Evals |
| Walmart | Principal, Data Architect | Retail | 8 | Agent orchestration · Agent research · Vector DB · LLM observability · Guardrails |
| Harvey | Senior Software Engineer, Fullstack - New Verticals | AI Frontier | 8 | Agent orchestration · Tool use · Evals · Guardrails · LLM observability · Model serving |
| Glean | Forward Deployed Product Manager | Enterprise | 8 | Agent orchestration · Vector DB |
| Glean | Forward Deployed Product Manager | Enterprise | 8 | Agent orchestration · Vector DB |
| Target | Sr Data Scientist - Advanced Machine Learning | Retail | 8 | Multimodal · Fine-tuning · LLM observability · Vector DB |
| Capital One | Senior Lead AI Engineer (FM Hosting) | Banking | 8 | Model serving · Inference infra · Fine-tuning · Guardrails · Vector DB · LLM observability |
| Microsoft | Sr Research Scientist | Big Tech | 8 | Code gen · Evals · Fine-tuning · Inference infra · Model serving · LLM observability |
| JPMorgan Chase | Investment Risk & Analytics - Quant Modeling Sr. Associate | Banking | 8 | LLM observability · Model serving · Agent orchestration |
| Whatnot | LLM Platform Engineer | Consumer | 8 | Agent orchestration · Evals · LLM observability · Model serving · Inference infra |
| JPMorgan Chase | AI/ML Engineer – Agentic Private Bank Engineer , Vice President | Banking | 8 | Agent orchestration · LLM observability · Fine-tuning · Model serving |
| Samsara | AI Engineer | Enterprise | 8 | Agent orchestration · Vector DB · LLM observability · Model serving |
| Celonis | Principal AI Deployment Architect | Data AI | 8 | Fine-tuning · Model serving · Agent orchestration · LLM observability |
| Celonis | Lead AI Deployment Architect | Data AI | 8 | Agent orchestration · Model serving |
| Amazon | Sr Software Development Engineer , AXU | Big Tech | 8 | Agent orchestration · LLM observability · Model serving · Inference infra · Guardrails · Agent research |
| MetLife | Lead Data Scientist | Insurance | 8 | Model serving · Inference infra · Fine-tuning · Vector DB |
| Suki AI | Senior Manager (AI Engineering) | Vertical AI | 8 | LLM observability · Agent orchestration · Model serving · Inference infra |
| Lila Sciences | Machine Learning Engineer II / Senior Machine Learning Engineer I, Physical Sciences | AI Frontier | 8 | Model serving · Inference infra · LLM observability · Multimodal |
| Cresta | Senior Forward Deployed Engineer (AI Agent) | Vertical AI | 8 | Agent orchestration · Tool use · LLM observability · Model serving |
| Celonis | Senior Applied Value Engineer | Data AI | 8 | Agent orchestration · LLM observability · Guardrails · Tool use · Fine-tuning |
| Samsara | AI Engineer | Enterprise | 8 | Agent orchestration · Vector DB · LLM observability · Tool use |
| Cloudflare | Machine Learning Engineer | Enterprise | 8 | Agent orchestration · Vector DB · Fine-tuning · Model serving · LLM observability |
| Capital One | Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) | Banking | 8 | Agent orchestration · Guardrails · LLM observability · Vector DB · Fine-tuning · Inference infra · Model serving |
| Capital One | Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) | Banking | 8 | Model serving · Inference infra · Guardrails · Vector DB · Fine-tuning · LLM observability · Evals · Agent orchestration |
| Capital One | Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) | Banking | 8 | Model serving · Inference infra · Guardrails · Vector DB · Fine-tuning · Evals · LLM observability · Agent orchestration |
| Workday | Machine Learning Engineer - Evisort | Enterprise | 8 | Model serving |
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.