1

Retrieval Augmented Generation Rag Jobs in California

Senior AI Engineer - LLM, RAG

Palo Alto, CA · On-site

$123K - $168K/yr

They are seeking a Senior AI Engineer to lead the development of Retrieval-Augmented Generation ... Responsibilities : • Lead the architecture and development of RAG systems that combine LLMs (e.g ...

Senior AI Engineer - LLM, RAG

Palo Alto, CA · On-site

$123K - $168K/yr

They are seeking a Senior AI Engineer to lead the development of Retrieval-Augmented Generation ... Responsibilities : • Lead the architecture and development of RAG systems that combine LLMs (e.g ...

Senior AI Engineer - LLM, RAG

Palo Alto, CA · On-site

$123K - $168K/yr

They are seeking a Senior AI Engineer to lead the development of Retrieval-Augmented Generation ... Responsibilities : • Lead the architecture and development of RAG systems that combine LLMs (e.g ...

Senior Agentic AI Engineer

Long Beach, CA

$114K - $156K/yr

This role focuses on agentic workflows, retrieval-augmented generation (RAG), tool orchestration, evaluation, and production deployment of GenAI systems. You will work at the intersection of LLMs ...

Software Engineer (Java + GenAI)

San Jose, CA · On-site

$60.75 - $83.25/hr

... Retrieval-Augmented Generation (RAG) - Vector databases - Prompt engineering - Large Language Models (LLMs) - Application: Send suitable profiles and contact details to rams@vensoft.com

Senior Agentic AI Engineer

Long Beach, CA · On-site +1

$87K - $189K/yr

This role focuses on agentic workflows, retrieval-augmented generation (RAG), tool orchestration, evaluation, and production deployment of GenAI systems. You will work at the intersection of LLMs ...

AI/ML Engineer

Burbank, CA · On-site

$111K - $153K/yr

Build and deploy RAG (Retrieval-Augmented Generation) pipelines * Integrate LLMs via APIs (Azure OpenAI preferred) into enterprise applications * Develop and orchestrate agentic AI workflows with ...

Advanced AI/ML: Strong expertise in Large Language Models (LLMs), including techniques like prompt engineering and Retrieval-Augmented Generation (RAG) * Coding Excellence: Proficiency in ...

Build and deploy RAG (Retrieval-Augmented Generation) pipelines * Integrate LLMs via APIs (Azure OpenAI preferred) into enterprise applications * Develop and orchestrate agentic AI workflows with ...

Data Engineer

Cupertino, CA · On-site

$141K - $169K/yr

... Retrieval Augmented Generation (RAG) techniques to enhance data analytics capabilities • Applying Machine Learning technologies for anomaly detection Minimum Qualifications Bachelor's degree in ...

Support advanced AI use cases, including LLM-based solutions, retrieval-augmented generation (RAG), and hybrid modeling approaches where appropriate * Collaborate with engineering teams to integrate ...

Support advanced AI use cases, including LLM-based solutions, retrieval-augmented generation (RAG), and hybrid modeling approaches where appropriate * Collaborate with engineering teams to integrate ...

next page

Showing results 1-20

Retrieval Augmented Generation Rag information

What are popular job titles related to Retrieval Augmented Generation Rag jobs in California? For Retrieval Augmented Generation Rag jobs in California, the most frequently searched job titles are:
What job categories do people searching Retrieval Augmented Generation Rag jobs in California look for? The top searched job categories for Retrieval Augmented Generation Rag jobs in California are:
What cities in California are hiring for Retrieval Augmented Generation Rag jobs? Cities in California with the most Retrieval Augmented Generation Rag job openings:

GenAI Engineer (RAG Specialist)

K&K Global Talent Solutions Inc.

Mountain View, CA • On-site

Other

Posted 10 days ago


Job description

Role Summary:


Focuses on implementing retrieval-augmented generation (RAG) pipelines, integrating LLMs with structured/unstructured data sources, and fine-tuning models for specific use cases.

Key Skills:

  • LangChain, LlamaIndex (formerly GPT Index), RAG architectures
  • OpenAI, HuggingFace models, Azure OpenAI Service
  • Prompt engineering, embeddings (e.g., FAISS, Pinecone)
  • Fine-tuning and model adaptation for domain-specific datasets
  • Python, RESTful APIs, orchestration frameworks.