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Retrieval Augmented Generation Jobs in Virginia (NOW HIRING)

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 ...

Purple Drive

Gen AI Engineer [Python, LLM]

Mclean, VA · On-site

Retrieval-Augmented Generation (RAG) * Ensure performance, scalability, and reliability of AI systems Agent Development & Orchestration * Program and orchestrate multi-agent systems * Build custom ...

Accenture Federal Services

AI Engineer

Arlington, VA · On-site

... deploy Retrieval-Augmented Generation (RAG) solutions and AI orchestration frameworks • Manage Kubernetes-based AI deployments and ensure seamless integration with OpenAI-compatible APIs • ...

ECS

Senior AI Engineer

Falls Church, VA · On-site

$111K - $153K/yr

This role leverages machine learning, natural language processing, and retrieval-augmented generation techniques to automate mission-critical workflows, accelerate request resolution, and strengthen ...

ECS

Sr. Data Scientist

Fairfax, VA · On-site

$175K - $205K/yr

In this role, you will design and optimize next-generation search and retrieval experiences using Elasticsearch, Vector Search, and Retrieval-Augmented Generation (RAG) techniques to improve ...

Minfy

Senior AI / LLM Engineer

Mclean, VA · On-site

$107K - $147K/yr

Retrieval augmented generation over large, real-world enterprise data is a prominent part of the work, alongside platform integration and LLM-driven analysis. You will set technical direction within ...

Amivero

AI Engineer

Reston, VA · On-site

$75K - $190K/yr

Develop scalable Retrieval-Augmented Generation (RAG) architectures that improve response quality, accuracy, explainability, and contextual relevance. * Engineer and optimize prompt orchestration ...

Amivero

AI Engineer

Reston, VA

Develop scalable Retrieval-Augmented Generation (RAG) architectures that improve response quality, accuracy, explainability, and contextual relevance. * Engineer and optimize prompt orchestration ...

Amivero

AI Engineer

Reston, VA · On-site

$75K - $190K/yr

Develop scalable Retrieval-Augmented Generation (RAG) architectures that improve response quality, accuracy, explainability, and contextual relevance. * Engineer and optimize prompt orchestration ...

Altagrove LLC

Data Science

Norfolk, VA · On-site

Design and implement Large Language Model (LLM) solutions, Retrieval-Augmented Generation (RAG) architectures, vector databases, and AI-enabled knowledge management capabilities. * Develop scalable ...

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Retrieval Augmented Generation information

What are the typical daily responsibilities of a Retrieval Augmented Generation engineer?

A Retrieval Augmented Generation engineer typically spends their day designing and implementing systems that combine information retrieval with advanced generative models, such as large language models. This includes fine-tuning models, integrating external data sources, developing vector search pipelines, and evaluating output quality. Collaboration with data scientists, machine learning engineers, and product teams is common to ensure the solutions meet user requirements and scale effectively. Additionally, RAG engineers often troubleshoot issues, monitor model performance in production, and stay informed about the latest advancements in AI and information retrieval.

What is a Retrieval Augmented Generation job?

A Retrieval Augmented Generation (RAG) job typically involves developing and optimizing AI systems that enhance text generation by incorporating external knowledge retrieved from relevant sources. Professionals in this field work on integrating retrieval mechanisms with large language models to improve the relevance, accuracy, and factual grounding of generated content. Common responsibilities include designing retrieval systems, fine-tuning language models, optimizing performance, and ensuring the seamless integration of factual data into AI-generated text. This role is highly interdisciplinary, involving expertise in natural language processing (NLP), machine learning, and information retrieval.

What are the key skills and qualifications needed to thrive in the Retrieval Augmented Generation position, and why are they important?

To thrive in a Retrieval Augmented Generation (RAG) engineering role, you need a solid background in machine learning, natural language processing (NLP), and experience with scalable information retrieval systems, typically supported by a relevant degree in computer science or a related field. Familiarity with tools such as Python, PyTorch or TensorFlow, vector databases, and search platforms like Elasticsearch is essential, along with practical experience deploying and tuning RAG pipelines. Strong problem-solving skills, a collaborative mindset, and effective communication abilities set outstanding professionals apart in this field. These competencies are crucial for designing, implementing, and optimizing hybrid retrieval-generation AI systems that address complex, real-world information needs.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Virginia? The most popular types of Retrieval Augmented Generation jobs in Virginia are:
What are popular job titles related to Retrieval Augmented Generation jobs in Virginia? For Retrieval Augmented Generation jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Retrieval Augmented Generation jobs in Virginia look for? The top searched job categories for Retrieval Augmented Generation jobs in Virginia are:
What cities in Virginia are hiring for Retrieval Augmented Generation jobs? Cities in Virginia with the most Retrieval Augmented Generation job openings:
Retrieval Augmented Generation jobs near you
Infographic showing various Retrieval Augmented Generation job openings in Virginia as of June 2026, with employment types broken down into 36% Full Time, 56% Part Time, and 8% Contract. Highlights an 71% Physical, 2% Hybrid, and 27% Remote job distribution.

AI/ML Engineer

Closure Technologies

Mclean, VA

Full-time

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.