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Rag Engineer Jobs (NOW HIRING)

Wipfli Advisory LLC

Senior AI Engineer

$142K - $191K/yr

As a Senior RAG Engineer, you will play a pivotal role in advancing our AI-driven functional requirements documentation platform, an enterprise application used across the firm to automate the ...

LTS

RAG and Evaluation Engineer

OR · On-site +1

LTS is seeking a RAG & Evaluation Engineer to join a small, senior engineering team applying frontier AI to one of the most consequential legacy systems still running in production today. The mission ...

LTS

RAG and Evaluation Engineer

LTS is seeking a RAG & Evaluation Engineer to join a small, senior engineering team applying frontier AI to one of the most consequential legacy systems still running in production today. The mission ...

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Rag Engineer information

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$59.5K

$90.5K

$153.5K

How much do rag engineer jobs pay per year?

As of Jun 28, 2026, the average yearly pay for rag engineer in the United States is $90,511.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,500.00 and $105,000.00 per year, depending on experience, location, and employer.

How to become a RAG engineer?

A RAG (Red, Amber, Green) engineer typically works in risk assessment or project management, requiring a background in engineering, data analysis, or related fields. Developing skills in data visualization tools, risk management methodologies, and obtaining relevant certifications can enhance qualifications for this role.

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.

Which 3 jobs will survive AI?

For a Rag Engineer, jobs that require complex manual skills, problem-solving, and hands-on work are more likely to survive AI automation. These include roles such as skilled trades like welding or machining, specialized maintenance technicians, and quality control inspectors. Such positions often depend on physical dexterity, judgment, and adaptability that AI and automation are less capable of replicating fully.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as AI research director, senior machine learning engineer, or AI executive, often requiring advanced skills in data science, programming, and deep learning. These roles usually involve leadership, strategic planning, and extensive experience, and they may be found in large tech companies or specialized AI firms.

What engineers make $500,000?

Senior engineers in specialized fields such as petroleum, aerospace, or software engineering can earn $500,000 or more annually, especially with experience, advanced skills, and in high-demand industries. Executive engineering roles or those with significant leadership responsibilities may also reach this compensation level.
More about Rag Engineer jobs
What cities are hiring for Rag Engineer jobs? Cities with the most Rag Engineer job openings:
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What job categories do people searching Rag Engineer jobs look for? The top searched job categories for Rag Engineer jobs are:
Rag Engineer jobs near you
Infographic showing various Rag Engineer job openings in the United States as of June 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $90,511 per year, or $43.5 per hour.
Senior AI Engineer - LLM, RAG

Senior AI Engineer - LLM, RAG

BrightAI Corporation

Palo Alto, CA • On-site

$122K - $168K/yr

Full-time

Posted 23 days ago

Key responsibilities

  • Lead the architecture and development of Retrieval-Augmented Generation (RAG) systems that combine large language models with structured and unstructured external information sources.

  • Develop AI-powered assistants to support technicians in diagnosing and resolving anomalies or failures in industrial settings.

  • Build pipelines to ingest, preprocess, and index large corpora of documents for semantic search and grounding.

Job description

Senior AI Engineer - RAG Systems
Bright.AI is a high-growth Physical AI company transforming how businesses interact with the physical world through intelligent automation. Our AI platform processes visual, spatial, and temporal data from billions of real-world events-captured across edge devices, mobile sensors, and cloud infrastructure-to enable intelligent decision-making at scale.
We are now hiring a Senior AI Engineer - LLM, RAG to lead the development of Retrieval-Augmented Generation (RAG) systems that harness the power of large language models (LLMs) and real-world knowledge sources. This role is pivotal to building next-generation intelligent assistants that help technicians and operators troubleshoot complex issues in industrial settings.
You'll work at the intersection of NLP, foundational models, and real-time information systems-developing intelligent tools that turn manuals, technician notes, and sensor data into actionable, conversational guidance for the physical world.
Responsibilities
  • Lead the architecture and development of RAG systems that combine LLMs (e.g., LLAMA, Mistral, Claude, GPT) with structured and unstructured external information sources.
  • Develop AI-powered assistants to support technicians in diagnosing and resolving anomalies or failures in factory, plant, or industrial settings.
  • Build pipelines to ingest, preprocess, and index large corpora of documents (manuals, logs, notes, procedures) for semantic search and grounding.
  • Customize and fine-tune foundational models to incorporate domain-specific language, tone, and logic for industrial troubleshooting scenarios.
  • Collaborate with product, data, and cloud teams to design scalable, privacy-compliant, and latency-sensitive LLM applications.
  • Design evaluation strategies to measure performance, accuracy, and user experience of RAG-enabled systems in production settings.
  • Stay up to date with the latest advances in LLM architectures, retrieval methods, and prompt engineering, and integrate emerging techniques into the product roadmap.
Educational Background
  • M.S. or Ph.D. in Computer Science, AI, Machine Learning, or a related field, with specialization in NLP or deep learning.
  • Strong research or applied background in large language models (LLMs) and retrieval-augmented generation (RAG) systems. Agentic RAG experience is highly desirable.
Required Skills & Expertise
  • 5+ years of experience in machine learning or AI with a strong focus on NLP, LLMs, or conversational AI.
  • Fluency with modern LLMs and open-source foundational models (e.g., LLAMA, Falcon, Mistral, GPT, Claude).
  • Experience building RAG pipelines with tools like LangChain, LlamaIndex, or custom vector database integrations, with at least one production grade system was built.
  • Fluency with prompt engineering, instruction tuning, or fine-tuning open-source models.
  • Deep understanding of document retrieval (semantic search, embedding generation, similarity metrics) and vector stores (e.g., FAISS, Weaviate, Pinecone).
  • Strong foundation in core machine learning techniques, including experience with reinforcement learning (RL) or decision-making models.
  • Proficiency with ML development frameworks such as PyTorch, Hugging Face Transformers, or similar. Strong Python programming is a must.
  • Experience integrating AI systems into real-world applications with user-facing interfaces and operational constraints.
  • Excellent problem-solving and critical thinking skills; ability to design solutions for complex, ambiguous problems.
  • Strong written and verbal communication skills, with ability to collaborate cross-functionally with engineers, product managers, and domain experts.
Bonus Qualifications
  • Experience applying LLMs in industrial or physical infrastructure settings (e.g., manufacturing, logistics, utilities, energy).
  • Knowledge of industrial control systems, maintenance workflows, or technician support processes.
  • Exposure to multimodal models or integrating textual data with sensor and/or time-series data.
  • Prior experience in a startup or a fast-paced environment building LLM-powered products from the ground up.
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About BrightAI

Sourced by ZipRecruiter

Industry

Software development

Company size

11 - 50 Employees

Headquarters location

San Francisco, CA, US

Year founded

2019

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