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, 2,037 active AI roles across 199 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.
2,037 active AI roles across 199 companies in our index reference RAG as of today.
The companies with the most active RAG listings are: Amazon (167 roles), JPMorgan Chase (146 roles), Google (78 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.
3504 AI roles tagged rag.
| Company | Title | Sector | AI score | Other tags |
|---|---|---|---|---|
| JPMorgan Chase | Applied AIML Associate- Python & Data Science Engineering | Banking | 8 | Vector DB · Model serving · Inference infra |
| GitLab | AI Engineer | Enterprise | 8 | Agent orchestration · Tool use · Guardrails · LLM observability |
| Intel | AI Algorithm Engineer Scientist | Semiconductors | 8 | Code gen · Agent orchestration · Fine-tuning · Multimodal · Audio & speech · Vision · Frontier research |
| Target | Sr Director Data Sciences | Retail | 8 | Agent orchestration · Search & ranking · Recommender systems · LLM observability · Evals · Model serving |
| Workday | Machine Learning Engineer III | Enterprise | 8 | Agent orchestration · Evals · Vector DB · Fine-tuning · Model serving · Recommender systems · Search & ranking · LLM observability |
| Capital One | Distinguished Engineer - Agentic AI | Banking | 8 | Agent orchestration · Agent research · Model serving |
| Adobe | Senior Data Science Engineer, GenAI Platforms & Data Infrastructure | Enterprise | 8 | Agent orchestration · Tool use · LLM observability · Model serving |
| Adobe | Machine Learning Engineer | Enterprise | 8 | Agent orchestration · Tool use · Evals · Model serving |
| Snowflake | Staff Software Engineer, Cortex AI Infrastructure | Data AI | 8 | Agent orchestration · Vector DB · Evals · Guardrails · LLM observability · Model serving · Inference infra |
| Snowflake | Sr. Enterprise Data & AI Architect | Data AI | 8 | Agent orchestration · LLM observability · Model serving |
| Apple | Senior iCloud Efficiency Engineer (GenAI & Agentic Systems) | Big Tech | 8 | Agent orchestration · Tool use · LLM observability · Guardrails |
| Microsoft | Applied Scientist II | Big Tech | 8 | Frontier research · Agent research · Multimodal · RL post-training |
| Microsoft | Member of Technical Staff, Applied AI Engineer | Big Tech | 8 | Agent orchestration · Evals · LLM observability · Model serving · Multimodal · Recommender systems · Search & ranking · Tool use |
| Mistral AI | Applied AI, Senior/Staff Forward Deployed Machine Learning Engineer - Morocco | AI Frontier | 8 | Fine-tuning · Vector DB · Agent orchestration · LLM observability · Model serving · Inference infra |
| JPMorgan Chase | Applied AI ML Director | Banking | 8 | Agent orchestration · LLM observability · Vector DB · Evals · Model serving |
| Software Engineer III, Machine Learning, Research and Products | Big Tech | 8 | Agent orchestration · LLM observability · Fine-tuning · Model serving · Audio & speech | |
| Forward Deployed Engineer II, Generative AI, Google Cloud | Big Tech | 8 | Agent orchestration · Multi-agent · Vector DB · Evals · LLM observability · Model serving | |
| Disney | Staff GenAI/ML Engineer (Emerging Tech & AI Automation) Project Hire | Media | 8 | Agent orchestration · Vector DB · Fine-tuning · Model serving · LLM observability · Evals |
| Capital One | Manager, Data Science - AI Software Engineering | Banking | 8 | Agent orchestration · Multi-agent · Fine-tuning · Tool use |
| Salesforce | Software Engineering PMTS | Enterprise | 8 | Agent orchestration · LLM observability · Vector DB · Fine-tuning · Inference infra · Model serving |
| Walmart | Senior, Data Scientist | Retail | 8 | Multimodal · Fine-tuning · Model serving |
| Expedia | Senior Software Development Engineer (GenAI, Agentic AI) | Hospitality | 8 | Agent orchestration · Tool use · Vector DB · Fine-tuning · Inference infra · Model serving · LLM observability · Guardrails |
| ByteDance | Software Engineer - AI Agent Memory Infrastructure | Big Tech | 8 | Agent orchestration · Vector DB · Multimodal · LLM observability · Model serving |
| Forward Deployed Engineer, GenAI, DACH, Google Cloud | Big Tech | 8 | Agent orchestration · Tool use · Evals · LLM observability · Vector DB · Model serving | |
| Product Manager, Gemini App, DeepMind | Big Tech | 8 | ||
| Rubrik | Software Engineer - Ruby AI | Enterprise | 8 | Agent orchestration · Tool use · Evals · LLM observability · Vector DB |
| Software Engineer, Applied AI | Big Tech | 8 | Agent orchestration · Tool use · Fine-tuning · Model serving · Evals · Audio & speech | |
| Senior Staff Technical Program Manager, AI Innovation and Research | Big Tech | 8 | Agent orchestration · Multi-agent | |
| Amazon | Applied Scientist, Sponsored Products Off-Search Homepage Team | Big Tech | 8 | Recommender systems · Search & ranking · Model serving · Fine-tuning · RLHF |
| Amazon | Applied Scientist-LLM, Buy For Me | Big Tech | 8 | Agent orchestration · Fine-tuning · Evals |