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
Walmart	Staff, Data Scientist – Conversational AI	Retail	9	Agent orchestration · Tool use · Evals · Guardrails · Fine-tuning · Model serving · LLM observability
Amazon	Sr. Applied Scientist, Ads AI Core Infrastructure	Big Tech	9	Agent orchestration · LLM observability · Evals · Code gen
ZoomInfo	Principal Product Manager, Agentic Tools & Orchestration	Enterprise	9	Agent orchestration · Tool use · LLM observability
Grafana Labs	Staff AI Engineer \| US \| Remote	Data AI	9	Agent orchestration · Tool use · LLM observability · Evals · Guardrails
Walmart	Principal, Data Scientist -- Agentic AI	Retail	9	Agent orchestration · Tool use · LLM observability · Fine-tuning · Model serving · Agent research · Multimodal · Vision · Code gen
Mistral AI	Applied AI, Forward Deployed Machine Learning Engineer - NYC/Palo Alto	AI Frontier	9	Fine-tuning · Agent orchestration · Vector DB · Model serving
NVIDIA	Senior AI ML Solution Engineer, AI-Native Development	Semiconductors	9	Agent orchestration · Tool use · Evals · Fine-tuning · Code gen
Adobe	Chief Architect for Adobe Intelligence Platform	Enterprise	9	Agent orchestration · Multi-agent · Tool use
Snowflake	AI Engineer - Cortex Code Quality	Data AI	9	Agent orchestration · Tool use · Evals · Guardrails · LLM observability · Code gen
Amazon	Applied Scientist III, AFT AI, Amazon AFT AI	Big Tech	9	Agent orchestration · Multimodal · Vision · LLM observability · Fine-tuning · Model serving · Agent research
Cohere	Product Manager, Agent Harness & Modelling	AI Frontier	9	Agent orchestration · Tool use · Evals · Agent research · Fine-tuning
Amazon	Applied Scientist II - AMZ9674020	Big Tech	9	Fine-tuning · Model serving · Frontier research · RL post-training · Evals
Cresta	Senior Machine Learning Engineer - Voice Experience	Vertical AI	9	Audio & speech · Fine-tuning · Model serving · Inference infra · Agent orchestration · Evals · LLM observability
Walmart	Principal, Data Scientist	Retail	9	Agent orchestration · Tool use · Vector DB · Evals · Model serving · Inference infra
Ramp	Agentic Operator, Growth Marketing	Fintech	9	Agent orchestration · Tool use · Evals · Guardrails · Fine-tuning · LLM observability
Apple	Evaluation & Insights Machine Learning Engineer	Big Tech	9	Evals · LLM observability · Guardrails · Fine-tuning · Model serving · Vector DB · Multimodal · RL post-training
OpenAI	Forward Deployed Engineer (FDE) - Seattle	AI Frontier	9	Model serving · Inference infra · LLM observability · Evals · Agent orchestration · Vector DB
Abridge	Software Engineer, GenAI	Vertical AI	9	Agent orchestration · Tool use · Vector DB · Model serving · LLM observability · Guardrails · Evals
JPMorgan Chase	Vice President — Principal Applied AI Data Scientist	Banking	9	Agent orchestration · Tool use · Vector DB · LLM observability · Multi-agent
Cohere	Forward Deployed Engineer, Agentic Platform	AI Frontier	9	Agent orchestration · Model serving
Axon	Senior Agentic AI Research Scientist	Enterprise	9	Agent orchestration · Multimodal · Vision · Vector DB · Inference infra · Model serving · Agent research
Cresta	Staff Machine Learning Engineer	Vertical AI	9	Agent orchestration · Tool use · Evals · Guardrails · LLM observability · Vector DB · Fine-tuning · Model serving · Agent research
Databricks	AI Engineer - FDE (Forward Deployed Engineer)	Data AI	9	Agent orchestration · Fine-tuning · Model serving · Evals
Sierra	Software Engineer, Agent	AI Frontier	9	Agent orchestration · Agent research · Evals · Model serving
Sierra	Agent Engineer, TLM	AI Frontier	9	Agent orchestration · Evals · Model serving
Snowflake	Principal Software Engineer - Snowflake Intelligence	Data AI	9	Agent orchestration · Tool use · Evals · Guardrails · LLM observability
Google	Forward Deployed Engineer IV, GenAI, Google Cloud	Big Tech	9	Agent orchestration · Model serving · LLM observability · Tool use
NVIDIA	Senior Manager, Engineering - Enterprise AI and Automation	Semiconductors	9	Agent orchestration · Tool use · Evals · Guardrails · Vector DB · Inference infra · Model serving
Amazon	Applied Scientist II, Ads AI Core Infrastructure	Big Tech	9	Agent orchestration · Vector DB · Fine-tuning · Inference infra · Model serving · Evals · LLM observability
Elastic	Elastic AI Engineer	Enterprise	9	Agent orchestration · LLM observability · 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.