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Retrieval Augmented Generation Jobs in Washington, DC

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.

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

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 ...

Showing results 21-40

Retrieval Augmented Generation information

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 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 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 are popular job titles related to Retrieval Augmented Generation jobs in Washington, DC?

For Retrieval Augmented Generation jobs in Washington, DC, the most frequently searched job titles 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 100% Full Time. Highlights an 100% Remote job distribution.

Sr. Data Scientist with Security Clearance

ECS

Fairfax, VA • On-site

$175K - $205K/yr

Other

Re-posted 23 days ago


Job description

Job Description Everforth ECS is seeking a Sr. Data Scientist to join our team in Arlington, VA. This position is contingent upon contract award. Are you passionate about building intelligent search and retrieval systems and applying GenAI to solve real-world data challenges? Join ECS, a leading provider of cloud, AI, data, and enterprise transformation solutions. 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 relevance, accuracy, and decision-making outcomes. We are seeking a Data Scientist focused on Search, RAG, and GenAI to support ECS's Professional Services. The ideal candidate enjoys working at the intersection of data science, search relevance, and large language models (LLMs), collaborating with customers and internal teams to deliver intelligent, high-impact solutions. You will play a key role in shaping search architectures, advising on best practices, and applying advanced AI techniques to enterprise-scale data sets. This role offers the opportunity to work with cutting-edge GenAI technologies while directly influencing customer success across diverse environments and use cases. Key Responsibilities * Design, implement, and optimize intelligent search solutions using Elasticsearch, including lexical, semantic, and vector-based search techniques. * Apply Retrieval-Augmented Generation (RAG) patterns to enhance LLM-driven applications with accurate, relevant, and contextual enterprise data. * Consult with customers to understand business objectives, data landscapes, and search challenges, translating requirements into effective AI-powered search strategies. * Build and refine embedding strategies, indexing approaches, and query workflows to improve relevance, precision, and recall. * Evaluate and integrate LLMs and GenAI capabilities into enterprise search and analytics use cases. * Collaborate with data, AI, and platform teams to align GenAI solutions with existing systems and operational workflows. * Provide strategic recommendations to improve search performance, result explainability, and overall user experience. * Lead knowledge-sharing sessions, technical workshops, and enablement activities related to GenAI, RAG, and advanced search techniques. * Serve as a trusted advisor for customers and internal stakeholders on emerging trends in AI-powered search and retrieval. * Stay current with advancements in Elasticsearch, GenAI, LLM tooling, and search relevance methodologies. Salary Range: $175,000-$205,000 Required Skills * Hands-on experience applying Elasticsearch to search, analytics, or data science use cases. * Strong understanding of search concepts including relevance tuning, indexing strategies, and query optimization. * Experience working with data science or AI-driven solutions in enterprise environments. * Familiarity with large-scale data platforms and cloud environments (AWS, Azure, or GCP). * Ability to translate complex technical concepts into clear guidance for customers and stakeholders. * Strong analytical, problem-solving, and communication skills. * Willingness and ability to travel to customer sites as needed. * Must be a U.S. Citizen and have an active Secret U.S. Security Clearance. * Bachelor's degree in Computer Science, Data Science, or a related field (or equivalent experience). Desired Skills * Master's degree or PhD in Computer Science, Data Science, or a related field. * Experience with Vector, Semantic, and Lexical Search techniques. * Hands-on experience designing or implementing Retrieval-Augmented Generation (RAG) solutions. * Familiarity with RAG evaluation concepts and frameworks (RAGAS, faithfulness, context precision, etc.) * Experience working with LLMs and GenAI frameworks and tooling. * Familiarity with AgentAI Builder or agent-based AI architectures. * Experience applying GenAI to enterprise search, observability, or security data. * Elastic Certified Engineer or related Elastic certifications. * Experience with Elasticsearch Enterprise Search use cases. * Familiarity with complementary search technologies (OpenSearch, Solr, Lucene). * Understanding of cybersecurity, observability, or operational data domains. * Experience working in consulting, professional services, or managed service environments. * Strong collaboration skills with the ability to mentor and guide team members. * Exposure to Agile or project-based delivery models. ECS Federal LLC is an equal opportunity employer and does not discriminate or allow discrimination on the basis any characteristic protected by law. All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, or local jurisdiction law. is the federal segment of , a $4B global organization with over 10,000 employees. Our nearly 3,500 professionals deliver advanced technology solutions in data and AI, cybersecurity, and enterprise transformation, serving defense, intelligence, and federal civilian agencies. Our work powers mission-critical outcomes, strengthens technology partnerships, and creates meaningful opportunities for our people. We are defined by a commitment to excellence in delivery, a culture of innovation, and an environment where talent can thrive and grow. We value: * Attracting and developing top talent and high-performing teams * Fostering a culture that is engaging, accountable, and mission-driven Meet the challenge. Make a difference with Everforth ECS!