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Remote Retrieval Augmented Generation Jobs in Washington, DC

System One

AI/ML Engineer

Mclean, VA · Remote

Remote Work Authorization: Must be able to work without sponsorship Clearance Requirement: Must be ... This position will focus on Retrieval-Augmented Generation, conversational AI, agentic workflows ...

Global Alliant Inc

AI Engineer

Rockville, MD · On-site +1

Remote/Hybrid (subject to contract requirements) Clearance: Must be eligible to obtain and maintain ... Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG)

Global Alliant Inc

AI Engineer

Rockville, MD · Remote

$140K/yr

Remote/Hybrid (subject to contract requirements) Clearance: Must be eligible to obtain and maintain ... Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG)

Global Alliant Inc

AI Engineer

Rockville, MD · Remote

Remote/Hybrid (subject to contract requirements) Clearance: Must be eligible to obtain and maintain ... Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG)

eSimplicity

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 ...

eSimplicity

Data Engineer II

Columbia, MD · On-site +1

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

Expression

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 ...

Ignite IT

Jr. AI Prompt Engineer

Ashburn, VA · On-site +1

Identify opportunities for advanced AI capabilities, automation, Retrieval-Augmented Generation (RAG), and agentic AI solutions and coordinate with technical teams as needed. Requirements * U.S.

Ignite IT

Jr. AI Prompt Engineer

Ashburn, VA · Remote

Identify opportunities for advanced AI capabilities, automation, Retrieval-Augmented Generation (RAG), and agentic AI solutions and coordinate with technical teams as needed. Requirements * U.S.

Hatch IT

AI/ML Engineer

Washington, DC · Remote

$130K - $170K/yr

Implement Retrieval-Augmented Generation (RAG), semantic search, and knowledge retrieval capabilities where appropriate. * Design AI orchestration workflows supporting distributed inference across ...

Interon IT Solutions

ServiceNow AI Developer

Chantilly, VA · Remote

$55.25 - $76/hr

Implement prompt engineering strategies and retrieval-augmented generation (RAG) patterns. * Train and tune machine learning models for classification, routing, and predictions. * Integrate AI agents ...

Steampunk

Data Scientist (Generative AI)

Mclean, VA · On-site +1

$125K - $160K/yr

Identify, clean, label, and synthesize high-quality datasets for model training, fine-tuning, or retrieval-augmented generation (RAG). * Design experiments to evaluate generative model behavior (e.g ...

System One

Be Seen First

LANGCHAIN AI QA ANALYST - 100% REMOTE

Washington, DC · Remote

$60 - $80/hr

Remote - offsite Hours: 40 hours a week Security Clearance: No clearance but must pass background ... Validate Retrieval-Augmented Generation (RAG) solutions utilizing Azure AI Search, Azure AI Foundry ...

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Remote Retrieval Augmented Generation information

What are the key skills and qualifications needed to thrive as a Remote Retrieval Augmented Generation Engineer, and why are they important?

To thrive as a Remote Retrieval Augmented Generation (RAG) Engineer, you need a strong background in machine learning, natural language processing, and information retrieval, often backed by a degree in computer science or a related field. Familiarity with tools and frameworks like PyTorch, TensorFlow, Hugging Face Transformers, and experience with retrieval systems such as Elasticsearch or FAISS are typically required. Problem-solving, effective communication, and adaptability are important soft skills for collaborating remotely and iterating on rapidly evolving AI solutions. These skills ensure the engineer can design, deploy, and optimize robust RAG systems that effectively combine retrieval and generation for high-quality AI outputs.

What is the difference between Remote Retrieval Augmented Generation vs Remote Data Scientist?

AspectRemote Retrieval Augmented GenerationRemote Data Scientist
CredentialsAI/ML knowledge, programming skillsStatistics, programming, domain expertise
Work EnvironmentAI development, NLP projectsData analysis, model building
Industry UsageAI, NLP, machine learningTech, finance, healthcare
Search & ComparisonOften compared for AI roles involving language modelsCompared for data analysis roles

Remote Retrieval Augmented Generation focuses on developing AI models that combine retrieval techniques with language generation, requiring expertise in AI, NLP, and programming. Remote Data Scientists analyze data, build models, and interpret results, often with statistical and domain knowledge. While both roles may work remotely and involve data handling, Retrieval Augmented Generation emphasizes AI model development, whereas Data Scientists focus on data analysis and insights.

What are some common challenges faced by professionals working in Remote Retrieval Augmented Generation roles, and how can they be addressed?

Professionals in Remote Retrieval Augmented Generation (RAG) roles often encounter challenges related to integrating diverse data sources, ensuring low latency in information retrieval, and maintaining the quality and relevance of augmented outputs. Coordinating effectively with distributed teams and adapting to rapidly evolving AI technologies are also common hurdles. To address these, staying current with best practices in data engineering, leveraging robust APIs, and participating in regular team check-ins can help ensure smooth collaboration and system performance.

What is Remote Retrieval Augmented Generation?

Remote Retrieval Augmented Generation (RAG) is an advanced AI technique that combines large language models with external information sources. In a remote RAG setup, the model retrieves relevant data from remote databases or APIs during the generation process, enhancing its responses with up-to-date or domain-specific knowledge. This approach is widely used in applications that require accurate, context-aware answers, such as chatbots, search engines, and virtual assistants. By leveraging remote retrieval, RAG systems can access a broader range of information without needing to store all data locally.
What are the most commonly searched types of Retrieval Augmented Generation jobs in Washington, DC? The most popular types of Retrieval Augmented Generation jobs in Washington, DC are:
What are popular job titles related to Remote Retrieval Augmented Generation jobs in Washington, DC? For Remote Retrieval Augmented Generation jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Remote Retrieval Augmented Generation jobs in Washington, DC look for? The top searched job categories for Remote Retrieval Augmented Generation jobs in Washington, DC are:
Remote Retrieval Augmented Generation jobs near you

AI/ML Engineer -- Generative AI Mission Systems

Rackner

Laurel, MD • On-site, Remote

$96K - $132K/yr

Full-time

Posted 11 days ago

Job description

AI/ML Engineer — Generative AI Mission Systems

Location: Mainly remote within the United States, with onsite collaboration in Laurel, Maryland, typically one day approximately every six weeks for team-wide sprint planning.
Clearance: Active final DoD Secret clearance required

This position supports a pending contract opportunity and is contingent upon contract award, with an anticipated start in November 2026.

Build Applied AI for Secure Mission Software

Help turn generative-AI concepts into dependable capabilities used within secure mission-planning and decision-support software.

At Rackner, you will integrate large language models, retrieval-augmented generation, agentic AI, prompt-engineering workflows, and inference pipelines into an established software application supporting a high-impact national-security mission. You will work across AI, software engineering, cybersecurity, DevSecOps, and customer technical teams to move capabilities beyond standalone demonstrations and into practical application workflows.

This role offers the opportunity to deepen your applied-AI experience, influence how emerging capabilities are designed and evaluated, and contribute to software where reliability, security, and mission usefulness matter.

This is a primarily remote role within the United States. Work will be performed using customer-provided systems, with virtual collaboration across the engineering team. Any classified work will be completed onsite at the customer location.

What You'll Do

  • Design, develop, test, and integrate AI-enabled software capabilities.
  • Build and integrate LLM-enabled capabilities into secure application workflows.
  • Develop or integrate retrieval-augmented generation capabilities.
  • Develop and support agentic-AI components and multi-step workflows.
  • Design and refine prompts, system instructions, and supporting AI workflows.
  • Build and maintain inference pipelines.
  • Connect AI capabilities with existing backend services and decision-support processes.
  • Evaluate AI outputs for grounding, reliability, accuracy, relevance, and mission usefulness.
  • Develop tests for AI-enabled functionality and support broader integration testing.
  • Demonstrate working prototypes and incorporate technical and user feedback.
  • Document AI designs, workflows, limitations, evaluation results, and implementation decisions.
  • Participate in code reviews, technical reviews, and security-remediation activities.
  • Collaborate with software engineers, security professionals, DevSecOps teams, and customer stakeholders.

What You Bring

  • A master's degree or Ph.D. in Artificial Intelligence, Machine Learning, Computer Science, or a related field, along with demonstrated experience working on or developing AI/ML capabilities.
  • At least four years of relevant AI/ML experience that includes work with large language models, retrieval-augmented generation, and prompt engineering.
  • Hands-on experience integrating LLM-enabled software and RAG capabilities into applications or workflows.
  • Developing or supporting agentic-AI capabilities and multi-step AI workflows.
  • Designing, building, or supporting inference pipelines.
  • Ability to evaluate AI-enabled capabilities and clearly document findings, design decisions, and results.
  • Testing and documenting AI-enabled software capabilities.
  • Ability to clearly explain your personal technical ownership and contributions.
  • Strong collaboration and technical-communication skills.

Preferred Background

Experience with several of the following can strengthen your fit:

  • Moving AI capabilities beyond coursework, personal projects, or demonstrations into operational software workflows.
  • Evaluating grounding, reliability, output quality, hallucinations, or other limitations of AI-enabled systems.
  • Integrating AI services with backend APIs or established software applications.
  • Secure software-development lifecycle and DevSecOps practices.
  • OpenShift, Kubernetes, CI/CD, or containerized application delivery.
  • Secure, restricted, disconnected, on-premises, or classified development environments.
  • Defense, government, aerospace, mission-planning, or other regulated environments.
  • Collaboration with software-engineering, cybersecurity, platform, and customer-facing technical teams.

Why Rackner

At Rackner, you will have the opportunity to build technology that supports critical defense and public-sector missions.

You will work on more than isolated AI experiments or prompt-engineering tasks. This role combines hands-on LLM integration, retrieval and agentic-AI development, secure software delivery, and close collaboration across AI, software, cybersecurity, DevSecOps, and mission-focused teams.

Rackner has delivered more than $30 million in recent federal awards and supports mission-critical work across defense, civilian, and public-sector environments. We are looking for an applied AI engineer who can build on that momentum by turning emerging generative-AI capabilities into secure, dependable software with meaningful mission impact.

Benefits & Professional Growth

  • Competitive compensation
  • Company-supported certifications aligned with current and future program work
  • 401(k) with 100% company match up to 6%
  • Medical, dental, vision, life, and disability coverage
  • Paid time off and company holidays
  • Remote-work support and home-office equipment plan
  • Fitness and wellness reimbursement
  • Weekly pay schedule
  • Professional-development and future growth opportunities

Apply

If you are an AI/ML engineer who wants to move beyond standalone prototypes and help integrate LLM, RAG, and agentic-AI capabilities into secure mission software, we would like to hear from you.