Which companies are hiring for RAG roles?

The companies with the most active RAG listings are: Amazon (167 roles), JPMorgan Chase (145 roles), Adobe (78 roles), Google (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 (5%).

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, 2,041 active AI roles across 203 companies in our index reference RAG. Hiring concentrates at the agents (85%) and application (5%) stages. Most common sectors: Enterprise, Big Tech, Banking.

Top hiring:

Function

All Engineering · 3013 Product · 333 Research · 94

Status

All Active only

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AI score Recently posted Company A–Z

3440 AI roles tagged rag.

Company	Title	Sector	AI score	Other tags
Amazon	Senior AI/ML Consultant, AWS Professional Services	Big Tech	7	Agent orchestration · Model serving · Fine-tuning
Amazon	Software Development Engineer, Rufus	Big Tech	7
Intel	GenAI Software Solutions Engineer	Semiconductors	7	Agent orchestration · Tool use · Model serving · LLM observability
Merck	Manager, ML Engineering	Pharma	7	Model serving · Inference infra · LLM observability
Deloitte	AI Data Engineer Manager	Consulting	7	Vector DB · LLM observability · Model serving
Adobe	Software Development Engineer	Enterprise	7	Agent orchestration · Tool use · Vector DB · LLM observability · Evals · Model serving
Deloitte	Lead Forward Deployed Engineer, Snowflake	Consulting	7	Agent orchestration · Tool use · Evals · Vector DB · Model serving
Deloitte	Lead Forward Deployed Engineer, Palantir	Consulting	7	Agent orchestration · LLM observability · Model serving · Evals
Apple	Full Stack Software Engineer - Camera & Photos Tools & AI Team	Big Tech	7	Agent orchestration · Tool use · LLM observability · Fine-tuning · Model serving · Vision · Multimodal
CVS Health	Principal Application Security Engineer – AI & Agentic Systems	Healthcare	7	Agent orchestration · Guardrails · LLM observability · Vector DB · Fine-tuning · Model serving · Agent research
BCG	Global Data Science Senior Manager – Chapter Lead	Consulting	7	Agent orchestration · LLM observability · Fine-tuning · Model serving
ZoomInfo	Principal Software Engineer	Enterprise	7	Agent orchestration · LLM observability · Vector DB · Model serving
OpenAI	Software Engineer, Core Science	AI Frontier	7	Agent orchestration · Vector DB · LLM observability
Oracle	ONA AI Agent Intern (Logistics Focus) - OVIP	Enterprise	7	Agent orchestration · Vector DB
Oracle	Senior Engineer – Data Platforms & Artificial Intelligence	Enterprise	7	Vector DB · Fine-tuning · LLM observability
Smartsheet	Senior Software Engineer I (Automation)	Seattle	7	Agent orchestration · Vector DB
Ford	Applied Data Scientist	Auto	7	Vector DB
Google	Customer Engineer, Generative AI (English, Portuguese)	Big Tech	7	Agent orchestration · Tool use · Guardrails · LLM observability · Fine-tuning · Multimodal · Audio & speech
Microsoft	Principal Software Engineer	Big Tech	7	Agent orchestration · LLM observability · Model serving · Semantic search
Google	Data and AI Consultant	Big Tech	7	Agent orchestration · LLM observability · Vector DB
JPMorgan Chase	Securitized Products Group - Quantitative Strategist (ML / LLM) - Tax Oriented Investment Associate	Banking	7	LLM observability · Fine-tuning · Model serving
Reddit	Senior Technical Product Manager, Ads ML Platform	Consumer	7	Model serving · Inference infra · Fine-tuning · Agent orchestration
GitLab	Senior AI Engineer	Enterprise	7	Agent orchestration · Tool use · Guardrails · Fine-tuning · Model serving
Honeywell	Lead AI Engr	Industrial	7	Agent orchestration · Fine-tuning · Model serving · Vector DB
Cursor	Director, Digital Support	Coding AI	7	Agent orchestration · LLM observability · Vector DB · Evals · Guardrails
Northrop Grumman	Software Engineer 2/3	Aerospace	7	Agent orchestration · Tool use · Evals · LLM observability
Amazon	Sr Mgr, Amazon Science Engineering, Academic Research Initiatives & Science Community	Big Tech	7	LLM observability · Model serving · Evals · Fine-tuning
Amazon	AI/ML Specialist Solutions Architect, Telecom, AGS US Specialist SA, TMEGS	Big Tech	7	LLM observability · Fine-tuning · Model serving
Amazon	Sr. PM-T, GenAI Experimentation, Selling Partner Communities (SPC)	Big Tech	7	Agent orchestration · Evals · Guardrails · LLM observability · Vector DB · Fine-tuning · Model serving · Recommender systems · Search & ranking · Multimodal · Code gen · Agent research
Amazon	Software Development Engineer II, AWS Invoicing	Big Tech	7	Agent orchestration · Evals

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?
2,041 active AI roles across 203 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 (145 roles), Adobe (78 roles), Google (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 (5%).
What sectors invest most in RAG?
The sectors with the most active RAG hiring are: Enterprise, Big Tech, Banking.