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.
2,014 active AI roles across 196 companies in our index reference RAG as of today.
The companies with the most active RAG listings are: Amazon (164 roles), JPMorgan Chase (144 roles), Google (77 roles), Adobe (73 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.
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, 2,014 active AI roles across 196 companies in our index reference RAG. Hiring concentrates at the agents (85%) and application (4%) stages. Most common sectors: Enterprise, Big Tech, Banking.
3505 AI roles tagged rag.
| Company | Title | Sector | AI score | Other tags |
|---|---|---|---|---|
| Microsoft | Principal Product Management | Big Tech | 8 | Agent orchestration · Evals · Frontier research |
| DoorDash | Software Engineer, Machine Learning Infrastructure - Gen AI | Consumer | 8 | Agent orchestration · Tool use · Evals · Guardrails · LLM observability · Vector DB · Fine-tuning · Inference infra · Model serving |
| JPMorgan Chase | Applied AI ML Lead [Multiple Positions Available] | Banking | 8 | Agent orchestration · LLM observability · Evals · Fine-tuning · Model serving |
| Senior Software Engineer, AI/ML, Geo and Gemini App | Big Tech | 8 | Agent orchestration · Tool use · Evals · LLM observability · Model serving · Inference infra | |
| Apple | Machine Learning Manager - AI, Search & Knowledge Platforms | Big Tech | 8 | Agent orchestration · LLM observability · Model serving · Search & ranking · Agent research |
| Amazon | Software Development Manager, Analytics and Data Management | Big Tech | 8 | Agent orchestration · Multi-agent · Evals · LLM observability · Model serving |
| Amazon | Data Scientist II, Alexa for Shopping Science UK | Big Tech | 8 | Agent orchestration · Multimodal · Recommender systems · LLM observability · Vector DB · Model serving · Inference infra |
| Amazon | Data Scientist II, RufusX Science UK | Big Tech | 8 | Agent orchestration · Multimodal · Recommender systems · Search & ranking · Inference infra · Model serving |
| Salesforce | Data Scientist | Enterprise | 8 | Agent orchestration · Fine-tuning · Evals · LLM observability |
| Workday | Principal AI Engineer - Evisort | Enterprise | 8 | Agent orchestration · Model serving |
| Workday | Sr Principal AI Engineer | Enterprise | 8 | Agent orchestration · Agent research · Vector DB · Fine-tuning · LLM observability |
| CrowdStrike | QA Engineer - GTM Applications (Remote, IND) | Enterprise | 8 | Agent orchestration · Evals · Guardrails · LLM observability · Vector DB · Fine-tuning · Model serving |
| GE Healthcare | Senior AI Application Engineer, Enterprise AI | Healthcare | 8 | Agent orchestration · Vector DB · Fine-tuning · Model serving · LLM observability |
| Salesforce | Agentforce Forward Deployed Engineer | Enterprise | 8 | Agent orchestration · Agent research · LLM observability · Vector DB |
| Pika Labs | Senior Software Engineer, Backend/Infra | AI Frontier | 8 | Agent orchestration · Tool use · LLM observability · Vector DB · Inference infra · Model serving · Multimodal |
| GECX AI Forward Deployed Engineer, Google Cloud | Big Tech | 8 | Agent orchestration · Tool use · Evals · LLM observability · Model serving | |
| GECX AI Forward Deployed Engineer I, Google Cloud | Big Tech | 8 | Agent orchestration · Tool use · Evals · LLM observability · Model serving | |
| Unity | Principal Forward Deployed Engineer | Enterprise | 8 | Agent orchestration · Tool use · Evals · LLM observability · Agent research |
| Cognite | Principal ML Engineer | Industrial | 8 | Model serving · Inference infra · Vision · Agent orchestration · Multimodal |
| Google Cloud Consulting Forward Deployed Engineer, Generative AI, Google Cloud | Big Tech | 8 | Agent orchestration · Vector DB · Evals · LLM observability | |
| Forward Deployed Engineering Manager III, GenAI, Google Cloud | Big Tech | 8 | Agent orchestration · Tool use · LLM observability | |
| JPMorgan Chase | Security Engineer III - AIML | Banking | 8 | Agent orchestration · Evals · Guardrails · LLM observability |
| Roblox | Senior Machine Learning Engineer, User Behavior | Consumer | 8 | Agent orchestration · Vector DB · Recommender systems · Model serving |
| Databricks | Specialist Solutions Architect - AI/ML | Data AI | 8 | Agent orchestration · Tool use · Guardrails · Vector DB · Evals · LLM observability · Model serving · Inference infra |
| Workday | Sr Machine Learning / AI Engineer / MLOps Engineer | Enterprise | 8 | Agent orchestration · Tool use · LLM observability · Fine-tuning · Model serving · Agent research · Guardrails |
| Salesforce | AI Engineer - Forward Deployed Engineer (Multiple Levels) | Enterprise | 8 | Agent orchestration · LLM observability · Fine-tuning · Model serving |
| Salesforce | AI Engineer - Forward Deployed Engineer (Multiple Levels) | Enterprise | 8 | Agent orchestration · LLM observability · Fine-tuning · Model serving |
| Salesforce | Forward Deployed Engineer | Enterprise | 8 | Agent orchestration · LLM observability · Tool use · Agent research |
| Salesforce | Forward Deployed Engineer | Enterprise | 8 | Agent orchestration · LLM observability · Vector DB · Fine-tuning · Model serving · Agent research |
| Salesforce | Forward Deployed Engineer | Enterprise | 8 | Agent orchestration · Agent research · LLM observability · Vector DB · Fine-tuning · Model serving |