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Ai Rag Jobs in Virginia (NOW HIRING)

AI Developer

Mclean, VA

$140K - $190K/yr

Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi-agent workflows, RAG pipelines, and specialized AI microservices. * Implement reusable AI components ...

Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi-agent workflows, RAG pipelines, and specialized AI microservices. * Implement reusable AI components ...

AI Engineer

Reston, VA · On-site

$75K - $190K/yr

Develop scalable Retrieval-Augmented Generation (RAG) architectures that improve response quality ... Support deployment of scalable and secure AI services using containers, serverless, and modern ...

AI Engineer

Reston, VA

$90K - $190K/yr

Develop scalable Retrieval-Augmented Generation (RAG) architectures that improve response quality ... Support deployment of scalable and secure AI services using containers, serverless, and modern ...

RAG pipelines * Vector databases * Knowledge graph integrations * Design and implement AI governance frameworks including: * Responsible AI * AI Guardrails * Model monitoring * Risk management

New

Develop scalable Retrieval-Augmented Generation (RAG) architectures that improve response quality ... Support deployment of scalable and secure AI services using containers, serverless, and modern ...

AI Engineer

Reston, VA

$75K - $190K/yr

Develop scalable Retrieval-Augmented Generation (RAG) architectures that improve response quality ... Support deployment of scalable and secure AI services using containers, serverless, and modern ...

Design and optimize Retrieval-Augmented Generation (RAG) pipelines for performance and scalability * Implement AI governance frameworks, including security guardrails and cost optimization strategies

Generative AI Architect

Reston, VA · On-site

$65.75 - $86.50/hr

Generative AI Architect About Ofinno: Ofinno is a leading research and development lab ... Your focus will be on utilizing LLMs and RAG technologies to enable advanced research capabilities ...

Generative AI Architect

Reston, VA · On-site

$65.75 - $86.50/hr

Generative AI Architect About Ofinno: Ofinno is a leading research and development lab ... Your focus will be on utilizing LLMs and RAG technologies to enable advanced research capabilities ...

... RAG) solutions and AI orchestration frameworks • Manage Kubernetes-based AI deployments and ensure seamless integration with OpenAI-compatible APIs • Develop and maintain Python-based AI ...

... RAG) solutions and AI orchestration frameworks • Manage Kubernetes-based AI deployments and ensure seamless integration with OpenAI-compatible APIs • Develop and maintain Python-based AI ...

... RAG) solutions and AI orchestration frameworks • Manage Kubernetes-based AI deployments and ensure seamless integration with OpenAI-compatible APIs • Develop and maintain Python-based AI ...

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Showing results 1-20

Ai Rag information

What are the key skills and qualifications needed to thrive as an AI Researcher, and why are they important?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What are some common challenges faced by AI RAG (Retrieval-Augmented Generation) engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.

What are AI RAGs?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

What cities in Virginia are hiring for Ai Rag jobs? Cities in Virginia with the most Ai Rag job openings:

$140K - $190K/yr

Full-time

Posted 15 days ago


Job description

We are looking for a highly skilled AI Developer to design, build, and optimize advanced AI solutions across predictive, generative, and autonomous system domains. This role requires strong hands-on engineering capabilities, deep familiarity with modern AI architectures, and the ability to translate mission needs into robust, production-ready AI capabilities. The Senior AI Developer will work across the full stack of AI development, from data ingestion and model experimentation to application integration, orchestration, and deployment, and will collaborate closely with product teams, LLMOps engineers, designers, and mission stakeholders.


  • Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi-agent workflows, RAG pipelines, and specialized AI microservices.
  • Implement reusable AI components, libraries, and APIs that streamline application development and accelerate delivery across programs.
  • Integrate AI models with enterprise systems, APIs, data platforms, vector databases, and cloud-native services to deliver scalable mission capabilities.
  • Drive iterative experimentation, prototyping, and model improvement cycles in collaboration with Data Scientists and AI Evaluation Scientists.
  • Design and implement advanced prompt strategies, context management layers, retrieval systems, and LLM orchestration logic.
  • Build scalable inference services, optimize model performance, and collaborate with LLMOps to enable robust deployment, monitoring, and continuous improvement.
  • Translate user needs and mission workflows into intuitive, reliable AI-powered features through active partnership with designers and product teams.
  • Implement secure-by-design and trustworthy AI practices, including safety guardrails, input sanitization, content filtering, and integration of evaluation metrics.
  • Contribute to internal AI frameworks, code patterns, and shared accelerators that raise delivery quality across the AI & Data Exploitation Practice.
  • Mentor junior developers, conduct code reviews, and support engineering excellence across multi-disciplinary AI delivery teams.
  • Stay current with emerging AI techniques, libraries, foundation models, and agent frameworks, evaluating their applicability to client missions.
  • You will contribute to the growth of our AI & Data Exploitation Practice!

  • Ability to hold a position of public trust with the U.S. government.
  • Bachelor’s degree and 3 years of relevant experience; OR
    • Master's degree and 1 year of relevant experience; OR
    • No degree and 7 years of relevant experience. 
    • Ability to hold a position of public trust with the U.S. government.
    • Bachelor’s degree and 3 years of relevant experience; OR
      • Master's degree and 1 year of relevant experience; OR
      • No degree and 7 years of relevant experience. 
  • Proficiency in Python; comfortable working across the AI/ML tooling ecosystem
  • Solid understanding of RAG architectures — chunking strategies, embedding models, vector stores, retrieval evaluation
  • Experience with at least one LLM orchestration framework (LangChain, LlamaIndex, LangGraph, CrewAI, or equivalent)
  • Strong prompt engineering skills — system prompts, few-shot design, chain-of-thought, and iterative refinement
  • Experience containerizing and deploying applications with Docker
  • Proficiency with Git and collaborative version control workflows
  • Ability to read and write REST APIs; comfortable integrating third-party services and models
  • Strong communication skills — you will interact with clients and translate fuzzy requirements into working systems

Preferred

  • Experience with cloud-native AI services, particularly AWS Bedrock for managed LLM inference
  • Familiarity with serverless compute (AWS Lambda) and managed ETL pipelines (AWS Glue) for data ingestion workflows
  • Working knowledge of vector and relational data stores including AWS RDS Postgres (pgvector) and OpenSearch
  • Container orchestration experience with Kubernetes for deploying and scaling AI services
  • CI/CD pipeline experience with Jenkins or similar build orchestration tools
  • Observability and logging experience for LLM pipelines — LangSmith, Arize, or equivalent
  • Familiarity with LLM evaluation frameworks such as RAGAS or DeepEval for measuring RAG and model quality
    • Hands-on experience with workflow automation platforms — n8n, Prefect, Airflow, or similar
    • Experience with MCP and tool-serving infrastructure (MCPO or similar)
    • Experience designing multi-agent systems with agent-to-agent coordination patterns
    • Experience with graph databases (Neo4j, Memgraph) and Graph RAG approaches
    • Prior consulting, agency, or client-delivery experience

Steampunk relies on several factors to determine salary, including but not limited to geographic location, contractual requirements, education, knowledge, skills, competencies, and experience. The projected compensation range for this position is $140,000 to $190,000.  The estimate displayed represents a typical annual salary range for this position. Annual salary is just one aspect of Steampunk’s total compensation package for employees. Learn more about additional Steampunk benefits here. 

Identity Statement

As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

Steampunk is a Change Agent in the Federal contracting industry, bringing new thinking to clients in the Homeland, Federal Civilian, Health and DoD sectors.  Through our Human-Centered delivery methodology, we are fundamentally changing the expectations our Federal clients have for true shared accountability in solving their toughest mission challenges.  As an employee owned company, we focus on investing in our employees to enable them to do the greatest work of their careers – and rewarding them for outstanding contributions to our growth. If you want to learn more about our story, visit http://www.steampunk.com.