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Rag Engineer Jobs in California (NOW HIRING)

Guide a team of engineers in building scalable, production-grade knowledge systems * Partner with ... and deploying RAG systems in production * Expertise with vector databases (Pinecone, Weaviate ...

About the role The AI Operations Engineer is responsible for building the central knowledge base ... Secure RAG Architecture: Design and maintain the vector databases and data pipelines that power ...

AIML Engineer Location: Santa Clara Valley, CA Work Model: Hybrid (3 days a week) Background ... Build and optimize RAG pipelines, vector databases, embeddings, and document-processing workflows.

Distinguished, Software Engineer

San Mateo, CA · On-site

$169K - $338K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are seeking a Distinguished Software Engineer with deep expertise in Generative AI, LLMs, Agentic and RAG frameworks to lead the design, development, and deployment of advanced AI systems. This ...

Distinguished, Software Engineer

Cupertino, CA · On-site

$169K - $338K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are seeking a Distinguished Software Engineer with deep expertise in Generative AI, LLMs, Agentic and RAG frameworks to lead the design, development, and deployment of advanced AI systems. This ...

Distinguished, Software Engineer

Fremont, CA · On-site

$169K - $338K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are seeking a Distinguished Software Engineer with deep expertise in Generative AI, LLMs, Agentic and RAG frameworks to lead the design, development, and deployment of advanced AI systems. This ...

Distinguished, Software Engineer

Mountain View, CA · On-site

$169K - $338K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are seeking a Distinguished Software Engineer with deep expertise in Generative AI, LLMs, Agentic and RAG frameworks to lead the design, development, and deployment of advanced AI systems. This ...

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Showing results 1-20

Rag Engineer information

See California salary details

$58.7K

$89.3K

$151.5K

How much do rag engineer jobs pay per year?

As of Aug 13, 2026, the average yearly pay for rag engineer in California is $89,326.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,600.00 and $103,600.00 per year, depending on experience, location, and employer.

What is the difference between Rag Engineer vs Textile Technician?

AspectRag EngineerTextile Technician
Required CredentialsEngineering degree, technical certificationsDiploma or degree in textiles or related field
Work EnvironmentFactories, manufacturing plants, R&D labsTextile mills, production facilities, quality control labs
Industry UsageDesigning and improving rag production processesMonitoring textile quality, testing fabrics

While both roles involve working within the textile industry, a Rag Engineer primarily focuses on the engineering aspects of rag production, process optimization, and machinery, whereas a Textile Technician concentrates on fabric testing, quality control, and ensuring textile standards are met. The roles often overlap in industry settings but differ in technical focus and responsibilities.

What job categories do people searching Rag Engineer jobs in California look for?

The top searched job categories for Rag Engineer jobs in California are:

What cities in California are hiring for Rag Engineer jobs?

Cities in California with the most Rag Engineer job openings:

Infographic showing various Rag Engineer job openings in California as of August 2026, with employment types broken down into 88% Full Time, 5% Part Time, 2% Temporary, and 5% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $89,326 per year, or $42.9 per hour.

GenAI Engineer (RAG Specialist)

K&K Global Talent Solutions Inc.

Mountain View, CA • On-site

Other

Re-posted yesterday


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.