Ai Chatbot Developer Jobs in Virginia (NOW HIRING)

GRAY WOLF SOLUTIONS, LLC Software Engineer/SME Location: Chantilly, VA HIGHLY DESIRED SKILLS AND DEMONSTRATED EXPERIENCE: • Demonstrated recent experience with the Sponsor’s Lean Agile methodology
• Experience evaluating, selecting, and integrating LLMs (e.g., OpenAI, open-source models) into
enterprise applications.
• Experience with vector databases, hybrid search (keyword + semantic), and relevance optimization.
• Ability to lead or mentor teams in adopting search + AI/LLM best practices (strong preference for
candidates who can elevate team capability, not just contribute individually). Tier 1 – Ideal Candidate • Has designed and implemented production-grade RAG systems (not just prototypes or demos).
• Deep hands-on experience with Elasticsearch, including relevance tuning, schema design, and scaling
strategies.
• Strong understanding of hybrid search (BM25 + vector search) and when to use each.
• Experience building end-to-end pipelines: data ingestion → chunking → embeddings → retrieval → LLM
integration.
• Comfortable making architectural decisions and leading technical direction for search + AI systems.
• Experience mentoring or upskilling other engineers in search or LLM-related technologies. Tier 2 – Acceptable Candidate • Has partial or adjacent experience with RAG, LLM integrations, or semantic search.
• Solid experience with Elasticsearch or similar search platforms, but may lack deep optimization
experience.
• Strong React + Node/Express background with ability to quickly ramp into search/AI domain.
• Has worked on APIs or systems that integrate external AI/ML services.
• Demonstrates strong learning ability and can become a team multiplier with guidance. Reject – Not a Fit • Primarily a generalist full-stack developer with no meaningful experience in search, information
retrieval, or LLM systems.
• Experience limited to basic “chatbot” integrations or plugins without understanding retrieval,
grounding, or data pipelines.
• No hands-on experience with Elasticsearch or equivalent search technologies.
• Lacks backend/API development depth (e.g., only front-end focused).
• Unable to explain how LLM outputs are grounded in data (i.e., no understanding of RAG concepts). KEY TASKS: • Participate in all Lean Agile scrums, sprints and grooming sessions.
• Consult and coordinate appropriately for problem resolution, task scheduling, new resource
requirements, and task clarification.
• Work in partnership with an integrated team of staff and contractors.
• Understand the cloud environments, such as AWS or Azure.
• Coordinate and collaborate with security, operations, engineering, testing and other teams to provide
system information and technical support.
• Design, develop and modify software systems.
• Document and track vendor software roadmaps for software and patch version updates.
• Unit test their software and perform code.
• Design and implement scalable search and retrieval systems leveraging Elasticsearch.
• Develop and integrate LLM-powered capabilities, including Retrieval-Augmented Generation (RAG)
pipelines REQUIRED SKILLS AND DEMONSTRATED EXPERIENCE: • Demonstrated experience working in Lean Agile Development environment.
• Demonstrated experience building or integrating LLM-based solutions, including RAG, semantic search,
or AI-assisted retrieval systems.
• Demonstrated experience developing detailed design and associated deliverables.
• Demonstrated experience translating customer and system requirements into design.
• Demonstrated experience designing system interfaces.
• Demonstrated experience developing Single Page Applications using React (modern hooks-based
architecture), HTML5, and CSS3.
• Demonstrated hands-on experience developing RESTful APIs using Node.js and Express (or comparable
modern backend frameworks).Demonstrated hands-on experience with and troubleshooting of Internet
and Web related protocols and technologies such as Tomcat, Nodejs, Web Services, or SSL.
• Demonstrated experience with testing platforms such as Jest or Karma.
• Demonstrated hands-on experience working with DevOps tools such as Git, Jenkins, or Nexus
• Demonstrated hands-on experience with Elasticsearch (index design, querying, relevance tuning, and
scaling).
• Demonstrated experience designing or implementing data pipelines to support search and/or RAG
workflows (e.g., ingestion, chunking, embeddings, vector search).