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Assistant Retrieval Augmented Generation Jobs in Virginia

Closure Technologies

AI/ML Engineer

Mclean, VA

Closure Technologies is seeking a AI/ML Engineer who will Implement and maintain Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) into applications, supported ...

Closure Technologies

AI/ML Engineer

Mclean, VA · On-site

Job Summary : Closure Technologies is seeking an AI/ML Engineer who will implement and maintain Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) into ...

Apavo Corporation

AI ML Engineer/Developer

VA · On-site

$325K/yr

Architect, build, and maintain enterprise-scale data platforms supporting vector databases, semantic search, Retrieval-Augmented Generation (RAG), Agentic AI systems, and large language model ...

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Assistant Retrieval Augmented Generation information

What is the difference between Assistant Retrieval Augmented Generation vs Data Analyst?

AspectAssistant Retrieval Augmented GenerationData Analyst
Required CredentialsKnowledge of AI, NLP, and retrieval systemsBachelor's in Statistics, Data Science, or related fields
Work EnvironmentTech companies, AI development teamsBusiness, finance, healthcare sectors
Industry UsageAI, machine learning, natural language processingData analysis, reporting, decision support

Assistant Retrieval Augmented Generation focuses on developing AI models that combine retrieval techniques with language generation, often requiring expertise in AI and NLP. Data Analysts interpret data to generate insights, primarily using statistical tools. While both roles involve working with data, Assistant Retrieval Augmented Generation is centered on AI model development, whereas Data Analysts focus on data interpretation and reporting.

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Assistant Retrieval Augmented Generation jobs near you
Infographic showing various Assistant Retrieval Augmented Generation job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 20% Part Time, 1% Temporary, and 2% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution.

AI/ML Engineer

Closure Technologies

Mclean, VA

Full-time

Re-posted 14 days ago

Job description

Closure Technologies is seeking a AI/ML Engineer who will Implement and maintain Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) into applications, supported by API development and optimizing data storage through Postgres schema refinement.

Clearance Requirement: TS/SCI with Polygraph

Key Responsibilities:

  • Implement and maintain RAG pipelines, including document processing, embedding generation, retrieval configuration, and prompt assembly.
  • Integrate LLMs into applications using available APIs and frameworks.
  • Develop and maintain REST API interactions to support data retrieval and system integration.
  • Design or refine Postgres schemas to improve data organization and query performance.

Required Qualifications:

  • Demonstrated ability to conduct independent technical research, evaluate emerging AI/ML approaches, and apply advanced analytical problem-solving comparable to PhD-level research environments.
  • Ability to rapidly learn and apply new AI/ML methodologies, tools, and frameworks in support of evolving mission requirements.
  • Experience developing AI/ML applications focused on Retrieval-Augmented Generation (RAG), semantic retrieval, LLM integration, or related AI workflows.
  • Strong proficiency in Python and modern AI/ML libraries, frameworks, and API integrations.
  • Active/current TS/SCI with required polygraph.
  • Willingness to work onsite full time.
  • US citizenship required.
  • Senior Labor Category: Minimum 8 years of experience with a Bachelor's degree; or 7 years of experience with a Masters degree; or 6 years of experience with a Doctorate

Preferred Qualifications:

  • Advanced research experience in machine learning, deep learning, natural language processing, generative AI, reinforcement learning, computer vision, or related disciplines.
  • Experience publishing research, contributing to open-source AI/ML initiatives, or leading experimental and prototype development efforts.
  • Familiarity with model evaluation frameworks, fine-tuning workflows, inference optimization, and AI observability/monitoring tools.
  • Experience with vector databases, AWS/cloud environments, Docker, and containerized AI/ML development workflows.
  • Experience designing and integrating REST APIs and scalable data architectures.

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