Which companies are hiring for RAG roles?

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).

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, 2,037 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.

Top hiring:

Function

All Engineering · 3068 Product · 342 Research · 94

Status

All Active only

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AI score Recently posted Company A–Z

3504 AI roles tagged rag.

Company	Title	Sector	AI score	Other tags
Block	Staff Machine Learning Engineer (Modeling), Support	Fintech	8	Agent orchestration · Fine-tuning · Inference infra · Model serving · Recommender systems
Instacart	Senior Software Engineer I — Agentic Analytics	Consumer	8	Agent orchestration · Evals · LLM observability
Apple	Data Scientist, EMEIA Sales	Big Tech	8	Agent orchestration · Agent research · LLM observability · Vector DB
JPMorgan Chase	Applied AI ML Lead	Banking	8	Agent orchestration · Tool use · Vector DB · LLM observability · Multi-agent
GEICO	Staff Applied Research Scientist	Insurance	8	Model serving · Recommender systems · LLM observability · Guardrails · Fine-tuning
Salesforce	Agentforce Forward Deployed Engineer B2C Commerce	Enterprise	8	Agent orchestration · LLM observability · Agent research · Tool use
LangChain	Solutions Architect (APAC)	Data AI	8	Agent orchestration · Inference infra · Model serving · Vector DB · Evals · Guardrails · LLM observability
Oracle	Software Developer 4	Enterprise	8	Model serving · Inference infra · Fine-tuning
Oracle	Software Developer 4	Enterprise	8	Model serving · Inference infra · Fine-tuning · LLM observability
ABBYY	Senior Product Manager, AI	Enterprise	8	Multimodal · Vision
Legora	Data & Analytics Intern	Vertical AI	8	Agent orchestration · Tool use · Evals · Guardrails · LLM observability · Vector DB
Anthropic	Applied AI Architect (Startups)	AI Frontier	8	Agent orchestration · Evals · LLM observability · Vector DB · Fine-tuning · Model serving
Databricks	AI Engineer - FDE (Forward Deployed Engineer) - U.S. Federal Sector	Data AI	8	Agent orchestration · Fine-tuning · Model serving · Evals
Apple	AI / Data Engineer	Big Tech	8	Agent orchestration · Tool use · LLM observability · Evals
Google	Forward Deployed Engineer, Google Cloud	Big Tech	8	Agent orchestration · Vector DB · LLM observability · Evals · Model serving · Inference infra · Fine-tuning · Multimodal
Airbnb	Senior Machine Learning Engineer, Community Support Engineering	Consumer	8	Agent orchestration · Fine-tuning · Evals · Guardrails · LLM observability
Amazon	Sr. AI Partner Solution Architect, ANZ Partner Team	Big Tech	8	Agent orchestration · Vector DB · LLM observability
Eli Lilly	Director, Discovery Bioinformatics Oncology	Pharma	8	Agent orchestration · Tool use · Fine-tuning · Multimodal
Verizon	Sr Engr Cslt-Data Science	Telecom	8	Agent orchestration · Tool use · LLM observability · Fine-tuning · Model serving
NVIDIA	Applied AI Engineer - VLSI Design	Semiconductors	8	Agent orchestration · Fine-tuning · Vector DB · LLM observability
Autodesk	Senior Machine Learning Engineer	Enterprise	8	Agent orchestration · Fine-tuning · Model serving · Search & ranking
Oura	Senior AI Engineer – Health Intelligence	Consumer	8	Agent orchestration · Tool use · Evals · Guardrails · LLM observability · Vector DB · Fine-tuning · Model serving · Recommender systems · Multimodal · Agent research
Apple	AI/ML Engineer (GenAI), G&A Solutions Engineering (GSE)	Big Tech	8	Agent orchestration · Fine-tuning · LLM observability · Multi-agent
Box	Forward Deployed Engineer	Enterprise	8	Agent orchestration · Model serving · LLM observability · Tool use
Box	Forward Deployed Engineer	Enterprise	8	Agent orchestration · Model serving · LLM observability · Tool use
Box	Forward Deployed Engineer	Enterprise	8	Agent orchestration · LLM observability · Model serving
Ford	Sr. Software Engineer, AI Specialist	Auto	8	Agent orchestration · Semantic search · Vector DB · LLM observability · Evals · Model serving
Google	Forward Deployed Engineer, Gen AI, Google Cloud	Big Tech	8	Agent orchestration · Fine-tuning · Evals · LLM observability
Amazon	Sr Manager, Applied Science, Alexa for Shopping (Rufus)	Big Tech	8	Agent orchestration · LLM observability · Evals · Guardrails · Multimodal · Tool use · Multi-agent
Amazon	Sr. Applied AI Solutions Architect - Public Sector, Amazon Connect	Big Tech	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?
2,037 active AI roles across 199 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 (167 roles), JPMorgan Chase (146 roles), Google (78 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.