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Remote Rag Jobs in Centreville, VA (NOW HIRING)

Booz Allen Hamilton, Inc.

AI/ML Engineer, Lead

Ashburn, VA · On-site +1

$104K - $138K/yr

Remote Work: Hybrid Job Number: R0246710 Location: Ashburn,VA,US Share job via: Share AI/ML ... Experience with LLMs, generative AI, RAG systems, and prompt engineering * Experience building ...

Eliassen Group

ETL Data Engineer

Tysons, VA · Remote

$70 - $88/hr

Description: Hybrid 3 days onsite / 2 days remote in Mclean, VA Our client seeks an ETL Data ... Knowledge of prompt engineering, RAG architectures, and context or memory management. * Experience ...

Danaher

Sr. AI Engineer

Washington, DC · On-site +1

$118K - $162K/yr

This position is remote in Eastern US. In this role, you will have the opportunity to ... RAG approaches, agentic frameworks, robotics. * Proven track record of successful end-to-end ...

Unissant

AI Developer Engineer

Ashburn, VA · Remote

This is a remote position. The ideal candidate is a hands-on AI/ML engineer who can develop ... Design, develop, and productionize RAG applications, chatbots, document translation and ...

UNISSANT

AI Developer Engineer

Ashburn, VA · Remote

This is a remote position. The ideal candidate is a hands-on AI/ML engineer who can develop ... Design, develop, and productionize RAG applications, chatbots, document translation and ...

UNISSANT

Senior Software Engineer

Ashburn, VA · Remote

$125K - $165K/yr

This is a remote position. The ideal candidate is a senior full-stack engineer who will provide ... Build user interfaces, APIs, middleware, data services, and back-end components for RAG/chatbot ...

System One

Be Seen First

AI/ML Solutions Architect

Mclean, VA · Remote

$130K - $216K/yr

Remote Hours: 40.0 Clearance: Must be able to obtain a Federal or DoD Public Trust clearance ... Augmented Generation (RAG) and evaluation, Re-ranking strategies, and retrieval quality ...

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Remote Rag information

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How much do remote rag jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for remote rag in Centreville, VA is $21.31, according to ZipRecruiter salary data. Most workers in this role earn between $17.88 and $22.64 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?

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

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 AI Solution Architect

Interon IT Solutions

Chantilly, VA • Remote

Contractor

Re-posted 12 days ago

Job description

#W2 Role
 
Role: Senior AI Solution Architect
Location: Remote
Experience: 10+ years preferred
Mandatory Skills: GCP, Vector Database, Agentic AI Frameworks, Python
 
Job Description
We are looking for a highly experienced and hands-on Senior AI Solution Architect to lead the design, development, and deployment of a scalable Agentic AI platform focused on knowledge-driven reasoning, enterprise transformation, and intelligent automation.
The ideal candidate should have strong experience in cloud modernization, AI architecture, enterprise API transformation, vector databases, Python development, and GCP-based AI/ML solutions. This role requires someone who can work closely with business, architecture, engineering, data, and cloud teams to transform enterprise services into AI-driven, searchable, and reusable capabilities through Knowledge Record Management, reasoning layers, orchestration frameworks, and agentic workflows.
 
Key Responsibilities
Lead the architecture, design, and implementation of a scalable Agentic AI platform for enterprise use cases.
Design AI-driven solutions focused on knowledge discovery, reasoning, orchestration, and enterprise automation.
Build and guide the development of reasoning and orchestration layers using Agentic AI frameworks.
Transform enterprise services, documents, and business knowledge into searchable APIs and reusable AI capabilities.
Design and implement Knowledge Record Management patterns to structure, classify, retrieve, and govern enterprise knowledge.
Build RAG-based and agentic workflows using vector databases, embeddings, retrieval pipelines, and LLM orchestration.
Develop AI solution architecture on Google Cloud Platform (GCP) using cloud-native services and scalable deployment models.
Lead cloud modernization and migration strategies to enable AI-first enterprise platforms.
Design secure, scalable, and reusable APIs to expose enterprise knowledge and services to AI agents.
Provide hands-on technical leadership in Python-based AI engineering, orchestration, and backend service development.
Evaluate and recommend AI frameworks, vector database platforms, embedding models, and orchestration patterns.
Partner with product owners, business stakeholders, architects, and engineering teams to convert business needs into AI solution designs.
Create architecture diagrams, technical design documents, API specifications, integration patterns, and implementation roadmaps.
Define best practices for responsible AI, security, access control, data privacy, observability, and governance.
Support proof-of-concepts, MVPs, production deployments, performance tuning, and platform scaling.
Mentor engineering teams on Agentic AI architecture, cloud-native design, and enterprise AI delivery practices.
 
Required Skills
10+ years of overall IT experience with strong experience in solution architecture, cloud architecture, AI/ML engineering, or enterprise application modernization.
Strong hands-on experience with Google Cloud Platform (GCP).
Strong experience designing and implementing Agentic AI frameworks and multi-agent workflows.
Hands-on experience with Python for AI engineering, backend services, orchestration, and API development.
Strong experience with vector databases such as Pinecone, Weaviate, Milvus, Chroma, FAISS, Vertex AI Vector Search, or similar platforms.
Experience building embeddings, semantic search, RAG pipelines, reasoning workflows, and knowledge retrieval systems.
Strong understanding of LLM-based solution design, prompt engineering, tool calling, function calling, and agent orchestration.
Experience building AI-driven APIs and transforming enterprise services into searchable, consumable, and reusable AI capabilities.
Strong understanding of cloud modernization, migration patterns, microservices, APIs, and enterprise integration.
Experience designing scalable, secure, and production-ready AI platforms.
Strong knowledge of data pipelines, metadata, document ingestion, chunking strategies, indexing, retrieval optimization, and knowledge governance.
Ability to define architecture standards, reusable design patterns, and technical implementation roadmaps.
Strong stakeholder management, communication, documentation, and leadership skills.
 
Preferred Skills
Experience with GCP services such as Vertex AI, BigQuery, Cloud Run, Cloud Functions, Cloud Storage, Pub/Sub, Cloud SQL, GKE, IAM, and API Gateway.
Experience with Agentic AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar tools.
Experience with Knowledge Graphs, ontology design, metadata management, taxonomy design, or enterprise knowledge management.
Experience designing reasoning/orchestration layers for enterprise GenAI platforms.
Experience with API management, REST APIs, GraphQL, event-driven architecture, and microservices.
Experience with MLOps, CI/CD, Docker, Kubernetes, Terraform, and cloud deployment automation.
Knowledge of security, privacy, governance, and compliance requirements for enterprise AI platforms.
 
Nice to Have
Experience with cloud migration and modernization from legacy platforms to GCP.
Experience implementing AI platforms for enterprise search, knowledge assistants, service automation, or intelligent workflow orchestration.
Exposure to model evaluation, LLM observability, hallucination controls, guardrails, and prompt/version management.
Experience working in financial services, healthcare, insurance, retail, or large enterprise environments.
 
Certifications
GCP Professional Cloud Architect, Professional Machine Learning Engineer, or related cloud/AI certifications are a plus.