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Rag Engineer Jobs in Berkeley, CA (NOW HIRING)

Applied AI Engineer

San Francisco, CA · On-site

$140 - $190/hr

This role owns the model-facing layer of our products: retrieval and RAG pipelines, agent planning and orchestration, multi-agent frameworks, and the context engineering that makes AI systems ...

You will work with LLMs, RAG, prompt engineering, multi-agent systems, and cloud AI platforms to develop production-grade machine learning applications. Key Responsibilities * Design, implement, and ...

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 ...

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 ...

They are seeking an AI/ML Engineer to build and maintain production-grade LLM pipelines, design RAG architectures, and integrate AI features into large-scale data pipelines. Responsibilities : • ...

AI Engineer

San Francisco, CA · On-site

$120 - $190/hr

Apply AI/ML technologies such as machine learning models, LLMs, embeddings, and basic agentic or RAG workflows under guidance from senior engineers. * Design, develop, and maintain high quality UI ...

Staff, Software Engineer

Hayward, CA · On-site

$143K - $286K/yr

We are seeking a Staff, 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 role ...

Translate AI capabilities -- RAG pipelines, agentic workflows, structured reasoning -- into interactions that feel natural to compliance practitioners * Partner with AI Engineers to define API ...

Staff, Software Engineer

San Mateo, CA · On-site

$143K - $286K/yr

We are seeking a Staff, 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 role ...

The ideal candidate will have strong full-stack engineering expertise combined with hands-on experience in LLMs, agentic workflows, RAG, AI orchestration, and modern cloud-native technologies. This ...

... RAG techniques using Python programming language. Qualifications : Required : • Experience - 5-7 Years • Experience in AI/ML development, with focus on OpenAI services, NLPs and LLMs • Ability ...

AI Engineer Location: San Francisco, CA Experience: 3+ years Employment Type: Full-time We are ... Develop RAG pipelines using vector databases and embedding models. Fine-tune and evaluate machine ...

Senior GenAI / Agentic AI Engineer (Python-heavy) Contract: 6 months (possible extension) Location ... The role will focus on building multi-agent systems, RAG pipelines, and AI-driven testing workflows ...

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Showing results 1-20

Rag Engineer information

See Berkeley, CA salary details

$72.9K

$110.8K

$188K

How much do rag engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for rag engineer in Berkeley, CA is $110,825.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,900.00 and $128,600.00 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.

How to become a rag engineer?

To become a rag engineer, you typically need a bachelor's degree in engineering, materials science, or a related field. Relevant skills include knowledge of manufacturing processes, quality control, and proficiency with industry tools and equipment; certifications in quality management or safety can also be beneficial. Gaining experience through internships or entry-level positions in manufacturing environments is important for career advancement.

What are popular job titles related to Rag Engineer jobs in Berkeley, CA?

For Rag Engineer jobs in Berkeley, CA, the most frequently searched job titles are:

What job categories do people searching Rag Engineer jobs in Berkeley, CA look for?

The top searched job categories for Rag Engineer jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Rag Engineer jobs?

Cities near Berkeley, CA with the most Rag Engineer job openings:

Infographic showing various Rag Engineer job openings in Berkeley, CA as of August 2026, with employment types broken down into 92% Full Time, 4% Part Time, and 4% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $110,825 per year, or $53.3 per hour.

Applied AI Engineer

Zof AI

San Francisco, CA • On-site

$140 - $190/hr

Other

Posted 7 days ago


Job description

Zof AI is seeking an Applied AI Engineer to build product features on top of frontier model APIs. This role owns the model-facing layer of our products: retrieval and RAG pipelines, agent planning and orchestration, multi-agent frameworks, and the context engineering that makes AI systems reliable in production. If you have worked as a GenAI Engineer, LLM Engineer, RAG Engineer, or Algorithm Engineer, this is that discipline at Zof AI. The ideal candidate has shipped LLM-powered features to real users and treats quality, cost, and latency as engineering constraints, not afterthoughts.

Engineering · Mid to Senior · Full-time · On-site · San Francisco, CA

Responsibilities
  • Design and build product features on top of frontier model APIs.
  • Build and tune retrieval and RAG pipelines end to end.
  • Design agent planning, tool use, and multi-agent orchestration.
  • Own prompt and context engineering as a disciplined, tested practice.
  • Wire evals into the development loop so quality is measured, not assumed.
  • Optimize the cost, quality, and latency of AI features in production.
  • Collaborate with product and engineering to ship reliably and fast.
  • Own model-layer systems from design through production.
Requirements
  • Experience shipping LLM-powered features to production.
  • Strong software engineering foundation.
  • Working knowledge of retrieval, RAG, and agent patterns.
  • Fluency with the modern model API and tooling ecosystem.
  • Judgment about quality, cost, and latency trade-offs.
  • Clear written and verbal communication.
  • Comfort operating in a fast-moving environment.
  • Evidence of building high-quality technical work.
Nice to have
  • Experience with multi-agent frameworks or agent orchestration systems.
  • Experience building or using eval harnesses.
  • Experience with TypeScript, Python, Node.js, Postgres, or similar technologies.
  • Experience with fine-tuning or model adaptation.

Deep, hands-on experience building production features on top of LLM APIs is required

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