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Retrieval Augmented Generation Jobs in Washington, DC

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 ...

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 ...

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 ...

Integrate with large language models (LLMs) and generative AI (GenAI) using prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) techniques. * Implement MCP client and server ...

This position will focus on Retrieval-Augmented Generation, conversational AI, agentic workflows, traditional machine learning, natural language processing, graph analytics, and entity resolution.

This position will focus on Retrieval-Augmented Generation, conversational AI, agentic workflows, traditional machine learning, natural language processing, graph analytics, and entity resolution.

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Retrieval Augmented Generation information

What does a retrieval augmented generation engineer do?

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?

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 skills and qualifications are needed for retrieval augmented generation?

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 Washington, DC? The most popular types of Retrieval Augmented Generation jobs in Washington, DC are:
What job categories do people searching Retrieval Augmented Generation jobs in Washington, DC look for? The top searched job categories for Retrieval Augmented Generation jobs in Washington, DC are:
Infographic showing various Retrieval Augmented Generation job openings in Washington, DC as of August 2026, with employment types broken down into 64% Full Time, 33% Part Time, and 3% Contract. Highlights an 62% Physical, 3% Hybrid, and 35% Remote job distribution.

Senior Applied AI Engineer - Software Engineering with Security Clearance

Neural Solutions

Columbia, MD • On-site

$204K - $247K/yr

Other

Posted 6 days ago


Job description


Join a fast-moving Tactical AI team developing production-quality AI applications that accelerate mission workflows through large language models (LLMs), retrieval-augmented generation (RAG), and modern software engineering practices. As part of this dynamic team, you will work directly with mission customers to design and develop AI-powered solutions that solve complex operational challenges. Responsibilities: * Design, develop, and maintain production AI-enabled software applications using Python and modern software engineering practices. * Architect and implement LLM-powered workflows, retrieval-augmented generation (RAG) pipelines, and AI agent capabilities that solve mission problems. Required Skills: * Production software development experience using Python. * Experience designing and developing distributed or backend software systems. * Experience building AI-enabled applications using LLMs, retrieval-augmented generation (RAG), AI agents, or similar technologies. Nice to Have: * Experience with Model Context Protocol (MCP), PydanticAI, LangChain, LlamaIndex, or similar AI frameworks. * Experience deploying applications using Docker, Kubernetes, or containerized environments. Experience Required: 12 years with Bachelor's degree in a technical field, or 16 years without degree Location: Columbia, MD Clearance: TS/SCI with Polygraph required Salary Range: $204,000 - $247,000