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Retrieval Augmented Generation Rag Jobs (NOW HIRING)

System One

GenAI Context Engineer

Pittsburgh, PA · On-site

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. * Build and optimize semantic retrieval pipelines, vector search ...

System One

GenAI Context Engineer

Pittsburgh, PA · On-site

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. * Build and optimize semantic retrieval pipelines, vector search ...

XPath Solutions

Generative AI Engineer

Charlotte, NC

$60 - $72/hr

This role focuses on developing Agentic AI systems , Retrieval-Augmented Generation (RAG) , multimodal AI solutions , and high-performance LLM inference while integrating GenAI capabilities into ...

Berriehill Research

Senior AI Technologist

Albuquerque, NM · On-site +1

$50.50 - $65/hr

Working closely with business units, engineers, and functional teams, you will leverage applied AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), AI agents ...

Merican

Full Stack AI Engineer (Generative AI)

Design and implement Retrieval-Augmented Generation (RAG) architectures using enterprise data sources. * Integrate AI capabilities into existing Java, .NET, or Node.js enterprise applications.

Berriehill Research

Senior AI Technologist

Raleigh, NC · On-site +1

$48.75 - $63/hr

Working closely with business units, engineers, and functional teams, you will leverage applied AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), AI agents ...

Accord Technologies Inc.

GEN AI Architect

New York, NY · On-site

The ideal candidate will have a strong background in investment banking, hands-on experience with Microsoft Azure OpenAI, and expertise in Retrieval-Augmented Generation (RAG). Key Responsibilities:

Closure Technologies

AI/ML Engineer

Mclean, VA

Closure Technologies is seeking a AI/ML Engineer who will Implement and maintain Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) into applications, supported ...

ARA

Senior AI Technologist

Raleigh, NC · On-site

$48.75 - $63/hr

Working closely with business units, engineers, and functional teams, you will leverage applied AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), AI agents ...

Tekshapers Inc

Generative AI/ML Engineer

New York, NY · On-site

The ideal candidate will have a strong background in investment banking, hands-on experience with Microsoft Azure OpenAI, and expertise in Retrieval-Augmented Generation (RAG). Key Responsibilities:

BrightAI

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 ...

Cliff Services Inc

Qdrant Developer

Alpharetta, GA · On-site

Knowledge of RAG (Retrieval-Augmented Generation) architectures. * Experience integrating Qdrant with LLM frameworks such as LangChain or LlamaIndex. * Familiarity with REST APIs and microservices.

New

BrightAI

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 ...

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How much do retrieval augmented generation rag jobs pay per hour?

As of Jul 23, 2026, the average hourly pay for retrieval augmented generation rag in the United States is $20.25, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $21.15 per hour, depending on experience, location, and employer.
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Infographic showing various Retrieval Augmented Generation Rag job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $42,119 per year, or $20.2 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 17 days ago

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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