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 |
|---|---|---|---|---|
| Bank of America | VP - GenAI Quant Developer | Banking | 8 | Agent orchestration · Tool use · Evals · Guardrails · Vector DB · Fine-tuning · Model serving |
| Capital One | Distinguished AI Engineer (Agentic AI Platform) | Banking | 8 | Agent orchestration · Guardrails · Vector DB · LLM observability · Model serving |
| Apple | Staff Machine Learning Engineer – Ads Signals Intelligence & Information Retrieval | Big Tech | 8 | Recommender systems · Search & ranking · Fine-tuning · LLM observability · Multimodal |
| Gusto | Head of AI-Native Talent Systems | Fintech | 8 | Agent orchestration · Evals · Guardrails · LLM observability · Vector DB · Fine-tuning · Model serving · Recommender systems · Search & ranking · Interpretability · Synthetic data · Agent research |
| Walmart | Staff, Software Engineer | Retail | 8 | Recommender systems · Search & ranking · Agent orchestration · Vector DB · LLM observability · Model serving · Inference infra · Multimodal |
| Capital One | Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) | Banking | 8 | Agent orchestration · Fine-tuning · Inference infra · Model serving · Guardrails · LLM observability · Vector DB · Evals |
| Perplexity | Member of Technical Staff (Data Scientist) | AI Frontier | 8 | Agent orchestration · LLM observability |
| Perplexity | Member of Technical Staff (Analytics Engineer) | AI Frontier | 8 | Agent orchestration · LLM observability |
| Twilio | Principal, Product Manager - AI / LLM | Enterprise | 8 | Agent orchestration · Fine-tuning · LLM observability |
| Airtable | AI Agent Architect, Customer Experience | Enterprise | 8 | Agent orchestration · Guardrails · LLM observability · Tool use |
| Intercom | Senior Data Scientist AI Tooling | Enterprise | 8 | Agent orchestration · Tool use · Evals · Vector DB |
| Deloitte | Senior Consultant - GenAI Full Stack Developer | Consulting | 8 | Agent orchestration · Vector DB · LLM observability · Guardrails · Model serving · Tool use |
| Apple | Machine Learning Engineer - LLM | Big Tech | 8 | Agent orchestration · Tool use · Fine-tuning · Model serving · Vector DB · Multimodal · LLM observability |
| Lyft | Senior ML Software Engineer | Consumer | 8 | Model serving · Inference infra · Agent orchestration |
| Lyft | Senior ML Software Engineer | Consumer | 8 | Model serving · Inference infra · Fine-tuning · Agent orchestration |
| Writer | Software engineer, agents | AI Frontier | 8 | Agent orchestration · Agent research · LLM observability · Vector DB · Model serving · Tool use |
| Datadog | Staff AI Engineer - Notebooks | Enterprise | 8 | Agent orchestration · Tool use · Guardrails · Evals · Fine-tuning · Model serving · Inference infra |
| Stripe | Machine Learning Engineer, Stripe Assistant | Fintech | 8 | Agent orchestration · Tool use · Evals · Fine-tuning · LLM observability · Code gen |
| Datadog | Staff AI Engineer - Notebooks | Enterprise | 8 | Agent orchestration · Tool use · Guardrails · Evals · Fine-tuning · Model serving |
| Datadog | Staff AI Engineer - Notebooks | Enterprise | 8 | Agent orchestration · Tool use · Evals · Guardrails · Fine-tuning · Model serving |
| Microsoft | Senior Applied AI Engineer | Big Tech | 8 | Agent orchestration · Fine-tuning · Evals · LLM observability |
| Grafana Labs | Staff AI Engineer | US | Remote | Data AI | 8 | Agent orchestration · LLM observability · Tool use · Evals |
| Grafana Labs | Staff AI Engineer | Canada | Remote | Data AI | 8 | Agent orchestration · Tool use · LLM observability · Guardrails |
| Celonis | Applied Value Engineer | Data AI | 8 | Agent orchestration · Guardrails · LLM observability · Fine-tuning |
| LangChain | GTM Engineer | Data AI | 8 | Agent orchestration · LLM observability |
| Walmart | Principal, Software Engineer – GenAI Initiative | Retail | 8 | Agent orchestration · Fine-tuning · Model serving · Vector DB · Multimodal |
| Perplexity | Member of Technical Staff (Data Scientist, Evals) | AI Frontier | 8 | Evals · LLM observability · Vision · Tool use |
| Deloitte | Mgr, Product Management – (GenAI/AI Product Experience) | Consulting | 8 | Agent orchestration · Tool use · LLM observability · Guardrails |
| Crusoe | Staff Enterprise AI Automation Engineer | Data AI | 8 | Agent orchestration · Tool use |
| Anthropic | Applied AI Engineer | AI Frontier | 8 | Agent orchestration · Evals · Fine-tuning · 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.