Which companies are hiring for RAG roles?

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).

What AI lifecycle stage does RAG belong to?

RAG primarily belongs to the agents and application stages of the AI lifecycle. In current hiring, RAG roles concentrate at: agents (85%), application (4%).

What sectors invest most in RAG?

The sectors with the most active RAG hiring are: Enterprise, Big Tech, Banking.

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RAG

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.

Top hiring:

Function

All Engineering · 3068 Product · 343 Research · 94

Status

All Active only

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AI score Recently posted Company A–Z

3505 AI roles tagged rag.

Company	Title	Sector	AI score	Other tags
Anthropic	Research Engineer, Knowledge Team	AI Frontier	9	Agent orchestration · Fine-tuning · RL post-training · Evals · Search & ranking
Sierra	Software Engineer, Agent	AI Frontier	9	Agent orchestration · Tool use · Evals · LLM observability · Audio & speech · Multimodal
Anthropic	[Expression of Interest] Research Scientist / Engineer, Honesty	AI Frontier	9	Fine-tuning · Evals · RL post-training · LLM observability
Cohere	Member of Technical Staff, MLE (North)	AI Frontier	9	Agent orchestration · Tool use · Fine-tuning · LLM observability
Vectara	Machine Learning (ML) Engineer	Data AI	9	Agent orchestration · Fine-tuning · Multimodal · Model serving · Evals
Cresta	Senior Machine Learning Engineer	Vertical AI	9	Agent orchestration · Evals · LLM observability · Tool use · Model serving
Databricks	Staff GenAI Research Scientist - Retrieval	Data AI	9	Agent orchestration · Vector DB · LLM observability
Anthropic	Research Engineer, Knowledge Team	AI Frontier	9	Agent orchestration · Fine-tuning · RL post-training · Evals · Search & ranking
Instacart	Machine Learning Engineer, PhD Intern	Consumer	9	LLM observability · Fine-tuning · Inference infra · Model serving · Recommender systems · Search & ranking · Agent research · Evals
OpenAI	Research Engineer, Retrieval & Search, Applied Engineering	AI Frontier	9	Vector DB · Search & ranking · Model serving · LLM observability
Databricks	PhD GenAI Research Scientist Intern	Data AI	9	Frontier research · Fine-tuning · Synthetic data · Inference infra · Evals
Okta	Principal Product Manager, Marketing Technology AI	Enterprise	8	Agent orchestration · Guardrails · Evals
Cohere	Software Engineer, Adoption	AI Frontier	8	Agent orchestration · Tool use · Evals · Guardrails · LLM observability
Cognite	Applied AI Engineer	Industrial	8	Agent orchestration · Tool use · Vector DB · LLM observability
Amazon	Senior Applied Scientist, Sponsored Products and Brands	Big Tech	8	Fine-tuning · Recommender systems · Search & ranking · RLHF
Adobe	Machine Learning Engineer 5	Enterprise	8	Vision · Fine-tuning · Inference infra · Model serving · Multimodal
JPMorgan Chase	Lead Software Engineer -AI	Banking	8	Agent orchestration · Tool use · Evals · LLM observability
JPMorgan Chase	Lead Software Engineer -AI	Banking	8	Agent orchestration · Tool use · Evals · LLM observability
PitchBook	Manager, Engineering, AI & ML	Fintech	8	LLM observability · Fine-tuning · Vector DB · Model serving
JPMorgan Chase	Senior Director of Software Engineering	Banking	8	Agent orchestration · Code gen
JPMorgan Chase	Applied AI ML Vice President	Banking	8	Agent orchestration · Evals · Model serving
Grafana Labs	Senior AI Engineer \| Canada \| Remote	Data AI	8	Agent orchestration · Tool use · LLM observability · Model serving
Grafana Labs	Senior AI Engineer \| US \| Remote	Data AI	8	Agent orchestration · Tool use · LLM observability · Model serving
Google	Forward Deployed Engineer, Gen AI, Google Cloud	Big Tech	8	Agent orchestration · Tool use · Evals · Guardrails · LLM observability · Fine-tuning · Model serving
Google	Forward Deployed Engineer, DeepMind	Big Tech	8	Agent orchestration · Multimodal · Evals · LLM observability · Model serving
Amazon	Machine Learning Engineer , Amazon Customer Service	Big Tech	8	Model serving · Inference infra · Agent orchestration · Guardrails · LLM observability
Zillow	Principal Product Technologist	Consumer	8	Agent orchestration · Tool use · LLM observability
Autodesk	Senior Principal Data Scientist, AEC	Enterprise	8	Agent orchestration · Agent research · Tool use · LLM observability · Evals
ServiceTitan	Director, Data Science	Enterprise	8	Agent orchestration · Tool use · Evals · Guardrails · LLM observability · Fine-tuning · Model serving · Agent research
JPMorgan Chase	Agent Platform Engineer Product Solutions Vice President - Chief Data Analytics Office Fusion Platform	Banking	8	Agent orchestration · Tool use

Frequently asked questions

What is RAG in AI?
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.
How many AI roles reference RAG right now?
2,014 active AI roles across 196 companies in our index reference RAG as of today.
Which companies are hiring for RAG roles?
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).
What AI lifecycle stage does RAG belong to?
RAG primarily belongs to the agents and application stages of the AI lifecycle. In current hiring, RAG roles concentrate at: agents (85%), application (4%).
What sectors invest most in RAG?
The sectors with the most active RAG hiring are: Enterprise, Big Tech, Banking.