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Remote Rag Jobs in Arlington, VA (NOW HIRING)

Forward Deployed Engineer

Washington, DC · On-site +1

$141K - $236K/yr

Knowledge of RAG, Hybrid RAG, MCP * Experience creating, maintaining, and communicating complex ... For Remote Opportunities), education and certifications as well as Federal Government Contract ...

AI/ML Engineer

Washington, DC · On-site +1

$130K - $170K/yr

Implement Retrieval-Augmented Generation (RAG), semantic search, and knowledge retrieval ... Hybrid or Remote with limited travel Benefits: Expression offers competitive salaries and benefits ...

Forward Deployed Engineer

Washington, DC · On-site +1

$141K - $236K/yr

Knowledge of RAG, Hybrid RAG, MCP * Experience creating, maintaining, and communicating complex ... For Remote Opportunities), education and certifications as well as Federal Government Contract ...

Data Engineer II

Columbia, MD · On-site +1

$93K - $100K/yr

Experience designing, implementing, and optimizing Retrieval-Augmented Generation (RAG) solutions ... Working Environment : eSimplicity supports a remote work environment operating within the Eastern ...

Solutions Architect

Washington, DC · Remote

$160K - $180K/yr

Now we're building an industry-leading knowledge management and Retrieval-Augmented Generation (RAG ... Remote first organization - 100% Company paid Health/Dental/Vision benefits for you and your ...

... RAG), Multi-Modal AI, and modern AI-enabled web applications. This role is remote/hybrid in the VA/MD/DC area. There may be occasional travel to client site in Washington D.C. Required Clearance:

AI Engineer

Washington, DC · On-site +1

$160K - $180K/yr

... RAG), Multi-Modal AI, and modern AI-enabled web applications. This role is remote/hybrid in the VA/MD/DC area. There may be occasional travel to client site in Washington D.C. Required Clearance:

Strong knowledge of agentic frameworks, orchestration tools, RAG, vector databases, API design, and ... Flexible to work remote with the ability to commute to the corporate office as needed Must have ...

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 ...

Solutions Architect

Washington, DC · Remote

$160K - $180K/yr

Now we're building an industry-leading knowledge management and Retrieval-Augmented Generation (RAG ... Benefits for Full Time Employees: - Remote first organization - 100% Company paid Health/Dental ...

AI Software Engineer - Remote

Reston, VA · On-site +1

$140K - $170K/yr

Hands-on experience with LLM APIs, prompt engineering, RAG architectures, and AI agent frameworks ... Opportunity for remote work. * A competitive salary and benefits package. * A casual, friendly, and ...

Design and integrate LLM applications, including multi-agent systems, tool-using agents, RAG ... performing, remote-first workforce. micro1 is an equal opportunity employer. All qualified ...

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Remote Rag information

See Arlington, VA salary details

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How much do remote rag jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for remote rag in Arlington, VA is $24.74, according to ZipRecruiter salary data. Most workers in this role earn between $20.72 and $26.25 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Rag, and why are they important?

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 (Retrieval-Augmented Generation) specialist?

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 (Responsible AI Governance) 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.
What job categories do people searching Remote Rag jobs in Arlington, VA look for? The top searched job categories for Remote Rag jobs in Arlington, VA are:
What cities near Arlington, VA are hiring for Remote Rag jobs? Cities near Arlington, VA with the most Remote Rag job openings:

Generative AI Engineer/Architect-REmote

HRC Global Services

Reston, VA • Remote

Full-time

Re-posted 26 days ago


Job description

We're looking for a Generative Al Engineer to architect and build next-generation Al products powered by large language models (LLMs), agent frameworks, and agentic pipelines. The role emphasizes building reliable, context-aware systems using Model Context Protocol (MCP) to manage and standardize model context, inputs, and tool interactions across agentic workflows.

Key responsibilities

* Design, prototype, and productionize LLM-based features and conversational agents using modern LLM APIs and frameworks.

* Implement and enforce MCP (Model,Context Protocol) patterns to structure prompts, context windows, tool calls, and metadata for consistent multi-turn and cross-tool behavior.

* Build and orchestrate agentic systems (planners, executors, tool chains) that integrate LLMs with external APis, knowledge bases, and tooling.

* Develop retrieval-augmented generation (RAG) pipelines, embeddings, and document indexing; manage vector DB integrations.

* Create evaluation pipelines and prompt engineering experiments; measure hallucination rates, factuality, latency, and

cost.

* Design and implement safety, guardrails, and monitoring: content filtering, adversarial testing, rate limits, and alerting for model failure modes.

* Optimize inference cost and latency across providers and on-prem hosts (quantized models, batching, caching).

* Build CI/CD and reproducible workflows for model versions, prompt artifacts, and MCP schema migrations; document

MCP conventions and laternal best practices.

Required qualifications

* 3+ years ML engineering or applied Al experience, with 1-2+ years working directly with LLMs and generative systems.

* Hands-on experience with LLM APls and agent frameworks (eg, LangChain, Llamaindex, Haystack, or equivalent).

* Practical experience implementing or following a Model Context Protocol (MCP) - structuring context, metadata, prompt templates, tool interfaces, and context stitching across sessions.

* Strona Pvthon engineerina skills: experience buildina production-arade microservices and APIs.