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Remote Rag Jobs (NOW HIRING)

Newcode.ai

Senior RAG Engineer

New York, NY · Remote

$134K - $176K/yr

The role is fully remote. Work from anywhere in the EU. Requirements What You'll Do * Own the ... RAG systems real users depend on. Backend depth without production retrieval won't be enough for ...

Huzzle

AI Engineer - Remote

Implement prompt engineering strategies and retrieval-augmented generation (RAG) pipelines ... Experience working in remote or distributed teams is a plus. Benefits Competitive salary based on ...

Delan Associates, Inc

AI Lead Engineer (Remote)

Dallas, TX · Remote

$104K - $138K/yr

AI Lead Engineer Dallas, TX (REMOTE) 15+ Years Must-Have Skills * Artificial Intelligence (AI ... Retrieval-Augmented Generation (RAG) * Embeddings & Vector Databases * Fine-tuning LLMs * Python

MRIoA

Quality Assurance Engineer (Remote)

Salt Lake City, UT · On-site +1

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

An award-winning remote work environment POSITION OVERVIEW Quality Assurance Engineer is a ... Design and execute validation strategies for AI/ML and Retrieval-Augmented Generation (RAG ...

Inficare Technologies

AI Engineer - Generative AI

Canada or Mexico (Remote) Job Type: Contract Experience: 5-10 years software development; 2-4 years ... Build RAG pipelines using embeddings and vector databases * Develop scalable REST APIs using ...

Zortech Solutions

GenAI Architect

Nashville, TN · Remote

Job Title GenAI Architect Duration: 6+ Months Location Nashville, TN Remote Work 100% Primary ... Experience with evaluation validation and refinement of results from GenerativeAI RAG based ...

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How much do remote rag jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for remote rag in the United States is $21.50, according to ZipRecruiter salary data. Most workers in this role earn between $18.03 and $22.84 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote RAG?

I'm sorry, but 'Remote Rag' does not appear to be a recognized professional occupation. Please provide a valid job title.

What is a Remote RAG?

A Remote RAG specialist is a professional who works with Retrieval-Augmented Generation (RAG) systems, typically in the field of artificial intelligence and machine learning. RAG combines traditional information retrieval techniques with generative models like large language models to provide more accurate and contextually relevant answers to user queries. Remote RAG specialists often build, fine-tune, and maintain these systems while working from a remote location. They may also work on integrating RAG models into applications, improving retrieval accuracy, and customizing outputs based on user needs.

What are some common challenges faced by professionals working in a remote RAG role?

Professionals in remote RAG roles often encounter challenges related to cross-functional collaboration and maintaining clear communication, especially when working across different time zones. Ensuring alignment on ethical AI standards and compliance requirements can be complex, as it typically involves coordinating with data scientists, legal teams, and business stakeholders. Staying current with evolving regulatory frameworks and best practices in AI governance is also essential, demanding continuous learning and adaptability. Building trust and rapport within a remote team can require extra effort, but leveraging digital collaboration tools and regular check-ins can help mitigate these challenges.
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Remote Rag jobs near you
Infographic showing various Remote Rag job openings in the United States as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 75% Physical, 6% Hybrid, and 19% Remote job distribution, with an average salary of $44,724 per year, or $21.5 per hour.

GenAI / Agentic AI Engineer (RAG & LLM Apps

ConglomerateIT LLC

Atlanta, GA • Remote

Contractor

Re-posted 17 days ago

Job description

Title:GenAI / Agentic AI Engineer (RAG & LLM Apps)
Location: US — Remote / Hybrid (multiple locations)
Type: Full-time or Contract (W2/C2C) 
Level: Mid–Senior (10+ Years Only)

We are hiring RAG-first GenAI engineers to build LLM-powered applications and agentic workflows for enterprise clients. This role centers on retrieval quality and reliable LLM integration as the foundation for agentic features.

What you'll do

  • Architect end-to-end RAG: chunking, embedding selection, hybrid/semantic search, re-ranking, citation and evaluation

  • Build LLM-powered microservices and APIs (FastAPI / REST)

  • Integrate and orchestrate LLMs (OpenAI, Claude, Gemini, Llama) into product and internal workflows

  • Add agentic behavior on top of RAG: tool-calling, multi-step task execution, guardrails, hallucination handling

  • Stand up and tune vector-store infrastructure; deploy and monitor in production

Must have

  • Strong Python

  • End-to-end RAG experience

  • Vector databases (Pinecone, Weaviate, pgvector, FAISS, or similar)

  • LLM API integration (OpenAI / Anthropic / Gemini / Llama)

  • LangChain and/or LlamaIndex

  • FastAPI / REST and one cloud (AWS, Azure, or GCP)

Nice to have

  • LangGraph, MCP, DSPy

  • Knowledge graphs / Neo4j, evals/LangSmith, MLOps

Founded in 2014, ConglomerateIT is a global leader in delivering innovative IT solutions and services. Headquartered in the USA with a presence in the UK, Canada, and India, we specialize in offering industry-leading expertise and cutting-edge products that help our clients maximize their technological investments. Our focus on best-in-class solutions, a highly knowledgeable team, and proactive talent mapping ensure we remain at the forefront of the IT industry.

ConglomerateIT is driven by our Center for Excellence and Innovation, an initiative dedicated to keeping us ahead in a rapidly evolving technology landscape. We understand that building strong relationships is key to our success, and this commitment has enabled us to partner with Fortune 500 companies and leading system integrators worldwide. Our ability to provide local talent on a global scale ensures that we can meet the contingent project requirements of our clients efficiently and effectively.