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 |
|---|---|---|---|---|
| NVIDIA | Principal GenAI Engagement Lead, Partner Platforms | Semiconductors | 8 | Agent orchestration · Tool use · Vector DB · Model serving · Multimodal |
| Adobe | Senior Manager, Forward Deployed AI Engineer | Enterprise | 8 | Agent orchestration · Fine-tuning · Model serving |
| Adobe | Machine Learning Engineer 50 | Enterprise | 8 | Agent orchestration · Fine-tuning · Model serving · LLM observability |
| Adobe | Senior Machine Learning Engineer, Express AI Foundations | Enterprise | 8 | Agent orchestration · Inference infra · Model serving · LLM observability · Vector DB |
| Adobe | Senior AI Engineer | Enterprise | 8 | Agent orchestration · LLM observability · Evals · Model serving |
| Adobe | Sr Machine Learning Engineer- ML Infrastructure & Data Platforms | Enterprise | 8 | Model serving · Inference infra · Multimodal · Vector DB |
| Adobe | Senior Agentic AI Engineer | Enterprise | 8 | Agent orchestration · Tool use · Evals · Guardrails · LLM observability · Vector DB · Model serving · Recommender systems · Search & ranking |
| Adobe | Senior Customer Facing Applied AI Engineer | Enterprise | 8 | Agent orchestration · Model serving · Inference infra · Evals · Guardrails · LLM observability |
| Adobe | Forward Deployed AI Engineer | Enterprise | 8 | Agent orchestration · Vector DB · Fine-tuning · Model serving · Multimodal · LLM observability |
| ElevenLabs | GTM Agentic Enablement Lead | AI Frontier | 8 | Agent orchestration · Tool use · LLM observability |
| Klaviyo | Senior AI Engineer, ARIA Team | Enterprise | 8 | Agent orchestration · Vector DB · Fine-tuning · Inference infra · Model serving · LLM observability · Guardrails |
| Capital One | Senior Lead AI Engineer,(MLX, Agentic AI, Gen AI platform Services) | Banking | 8 | Model serving · Inference infra · Guardrails · Vector DB · Fine-tuning · LLM observability · Evals |
| Capital One | Senior Lead AI Engineer (MLX, Agentic AI, Gen AI platform Services) | Banking | 8 | Model serving · Inference infra · Guardrails · Vector DB · LLM observability · Fine-tuning |
| Capital One | Lead AI Engineer (MLX, Agentic AI, Gen AI platform Services) | Banking | 8 | Model serving · Inference infra · Guardrails · Vector DB · LLM observability |
| JPMorgan Chase | Applied AI/ML - Vice President | Banking | 8 | LLM observability · Agent orchestration · Recommender systems |
| Oura | Staff AI Scientist | Consumer | 8 | Recommender systems · Search & ranking · LLM observability · Model serving · Inference infra |
| Celonis | Senior Value Engineer (Public Sector) - Sacramento, CA | Data AI | 8 | Agent orchestration · Guardrails · LLM observability |
| Apple | ML Engineer, Ai & Data Platforms | Big Tech | 8 | Agent orchestration · LLM observability · Model serving |
| JPMorgan Chase | Applied AI ML Lead | Banking | 8 | Agent orchestration · Tool use · LLM observability · Fine-tuning · Model serving · Inference infra |
| JPMorgan Chase | Principal Applied AI ML Engineer | Banking | 8 | Agent orchestration · Vector DB · Guardrails · Model serving · Inference infra · LLM observability · Tool use |
| Amazon | Sr. Applied Science Manager, AGI Information | Big Tech | 8 | LLM observability · Model serving |
| GEICO | Staff Engineer - Applied AI | Insurance | 8 | Agent orchestration · Vector DB · LLM observability · Model serving |
| Klaviyo | Senior Product Manager, AI (Customer Agent) | Enterprise | 8 | Agent orchestration · LLM observability |
| Senior Staff Machine Learning Engineer, GenAI Platform | Consumer | 8 | Agent orchestration · Tool use · LLM observability · Model serving · Inference infra | |
| Honeywell | Software Engr II | Industrial | 8 | Agent orchestration · Inference infra · Model serving · LLM observability |
| Amazon | Data Scientist, AWS Quick Data | Big Tech | 8 | Evals · Synthetic data · LLM observability |
| PayPal | Sr Machine Learning Engineer | Fintech | 8 | Agent orchestration · Tool use · Agent research · LLM observability · Fine-tuning · Model serving · Evals |
| Walmart | Staff, Data Scientist - Conversational AI | Retail | 8 | Agent orchestration · Tool use · Guardrails · LLM observability |
| Capital One | Sr. Lead AI Engineer (AI Foundations) | Banking | 8 | Model serving · Inference infra · Fine-tuning · Guardrails · Vector DB · LLM observability |
| Capital One | Lead AI Engineer (AI Foundations) | Banking | 8 | Model serving · Inference infra · Guardrails · Vector DB · Fine-tuning · LLM observability · Evals |
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.