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Retrieval Augmented Generation Rag Jobs (NOW HIRING)

Job Summary : Closure Technologies is seeking an AI/ML Engineer who will implement and maintain Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) into ...

AI Engineer

Santa Clara, CA · On-site

$56 - $61/hr

Experience architecting and implementing Retrieval-Augmented Generation (RAG) pipelines to enhance model performance using external knowledge sources, including document chunking, embedding ...

Integrate with large language models (LLMs) and generative AI (GenAI) using prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) techniques. * Implement MCP client and server ...

AI Lead

Chicago, IL · On-site

$144K - $177K/yr

The ideal candidate will bring deep expertise in Python, FastAPI, and Retrieval-Augmented Generation (RAG) solutions, with hands-on experience deploying scalable AI applications on Azure. This role ...

... Retrieval-Augmented Generation (RAG) pipelines, and Agent SDKs - Skilled in building and deploying AI/LLM systems in production environments - Familiarity with AI agents, including evaluation ...

Data Analyst

Phoenix, AZ · On-site

$100K - $110K/yr

... Retrieval-Augmented Generation (RAG), and Agentic AI technologies. Working within a highly regulated financial environment, you will contribute to building scalable data solutions and support AI ...

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

New Jersey /New York (Onsite) We are looking for a GenAI Engineer with strong hands-on experience building RAG (Retrieval-Augmented Generation) solutions and document vectorization pipelines. Must ...

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

As of Sep 2, 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 August 2026, with employment types broken down into 67% Full Time, 32% Part Time, and 1% Contract. Highlights an 65% Physical, 2% Hybrid, and 33% Remote job distribution, with an average salary of $42,119 per year, or $20.2 per hour.

Sr AI Developer/Agentic AI Engineer

Accord Technologies Inc.

Charlotte, NC • On-site

Contractor

Re-posted 22 days ago


Job description

Title: AI developer/Agentic AI Engineer
Location: Charlotte, NC
Duration: 12 months
Position type: W2 contract

 

Job Description :

We are seeking for highly skilled Software Engineer with strong expertise in modern Python development and Large Language Model (LLM) ecosystems.
This role focuses on building scalable, production-grade AI systems, leveraging advanced API development, retrieval-augmented generation (RAG), and agentic frameworks. 
You will work on cutting-edge AI solutions, contributing to the design, development, and deployment of intelligent systems within a distributed enterprise environment

Core Programming & Backend Development

  • Develop robust, scalable applications using Python (intermediate to advanced level)

  • Implement asynchronous programming patterns for high-performance systems

  • Design and build RESTful APIs using FastAPI

  • Write clean, maintainable, production-grade code

  • Develop and execute unit and integration tests

  • Debug and resolve issues in complex distributed systems

LLM Fundamentals & Prompt Engineering

  • Design and optimize prompts for various LLM use cases

  • Understand tokenization, context windows, and model limitations

  • Select appropriate models based on performance and cost trade-offs

  • Mitigate hallucinations and ensure grounded, reliable responses

Retrieval-Augmented Generation (RAG)

  • Build and maintain document ingestion and preprocessing pipelines

  • Implement chunking strategies (semantic, recursive, sliding window)

  • Generate and manage embeddings

  • Work with vector databases (e.g., pgvector)

  • Design hybrid search systems combining keyword (BM25) and semantic search

  • Optimize re-ranking and relevance tuning mechanisms

Agentic Frameworks & Orchestration

  • Design and implement multi-agent systems

  • Manage conversational and long-term memory

  • Build workflow orchestration pipelines for AI agents

Required Qualifications

  • Strong proficiency in Python with experience in asynchronous programming

  • Hands-on experience with FastAPI or similar frameworks

  • Experience building scalable backend systems

  • Solid understanding of LLM concepts and prompt engineering

  • Experience with RAG pipelines and vector databases (pgvector preferred)

  • Familiarity with distributed systems and debugging techniques

  • Experience with Docker and CI/CD pipelines