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Remote Rag Jobs in Richmond, VA (NOW HIRING)

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$17

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$23

How much do remote rag jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for remote rag in Richmond, VA is $21.28, according to ZipRecruiter salary data. Most workers in this role earn between $17.84 and $22.60 per hour, depending on experience, location, and employer.

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

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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

SENIOR AMAZON BEDROCK/RAG ENGINEER - Remote

Axyde Analytics

Midlothian, VA • Remote

$99K - $135K/yr

Full-time

Posted 14 days ago

Job description

Axyde Analytics seeks a senior Amazon Bedrock engineer to configure secure retrieval-augmented generation, document processing, structured extraction, source attribution, and policy-mapping capabilities for a federal analytics platform.

Responsibilities

  • Configure Amazon Bedrock managed Knowledge Bases and approved managed retrieval components.

  • Implement secure ingestion and indexing of approved websites, linked documents, PDFs, and enterprise data.

  • Configure foundation models, embedding models, chunking, retrieval, prompts, schemas, and guardrails.

  • Extract structured issues, requirements, entities, relationships, and exact supporting source excerpts.

  • Implement citation-backed responses and traceable mappings between source documents and Government directives.

  • Ensure prompts and Government data remain within the authorized environment and are not used to train external models.

  • Develop measurable evaluation criteria for extraction accuracy, retrieval quality, citation correctness, and hallucination control.

  • Support OCR and managed natural-language-processing services when approved.

  • Document exact models, versions, configurations, limitations, and dependencies.

  • Support live demonstrations, production hardening, monitoring, and continuous improvement.

Required Experience

  • Direct production experience with Amazon Bedrock and Bedrock Knowledge Bases.

  • Experience with managed web crawling, linked-document ingestion, parsing, embeddings, vector retrieval, structured extraction, and RAG evaluation.

  • Strong understanding of prompt security, model governance, guardrails, source attribution, and sensitive-data handling.

  • Experience implementing AI solutions in federal, healthcare, financial, or similarly regulated environments.

  • Ability to work exclusively within an approved AWS managed-service architecture.

Current Baseline

The current baseline includes Amazon Bedrock, managed Knowledge Bases, approved Bedrock-managed retrieval, Claude Sonnet, Titan Text Embeddings, Guardrails, S3, Step Functions, and AWS-native security and monitoring. Exact services, models, versions, and regions will be governed by Axyde’s final approved technical baseline.

Engagement

U.S. citizenship required. Remote within the United States. Immediate availability for proposal validation and demonstration development is preferred. Continued work is contingent upon award.