AI Software Engineer - TS​/SCI Polygraph

Regular Clearance Level Must Currently Possess:
Top Secret SCI + Polygraph Clearance Level Must Be Able to Obtain:
None Public Trust/Other

Required:

None Job Family:
Data Science and Data Engineering

Job Qualifications:

Skills:

Chatbots, Elastic Search, RAG Pipeline

Certifications:

None

Experience:

10 + years of related experience US Citizenship

Required:

Yes

Transform technology into opportunity as an AI Software Engineer (SME) with GDIT. We are seeking a hands‑on software engineer with expertise in designing, developing, and sustaining cloud‑enabled applications in Lean Agile environments to deliver secure, scalable, and maintainable mission‑critical customer systems. The role requires expertise in frontend and backend Web development and modern search engineering technologies, including Large Language Models (LLM), Retrieval‑Augmented Generation (RAG), and AI‑assisted retrieval system capabilities development.

• Participate in all Lean Agile scrums, sprint planning, and grooming sessions.
• Consult and coordinate with stakeholders for problem resolution, task scheduling, resource needs, and task clarification.
• Work in partnership with an integrated team of staff and contractors.
• Coordinate and collaborate with security, operations, engineering, testing, and other teams to provide system information and technical support.
• Understand and work within approved cloud environments (e.g., AWS).
• Design, develop, and modify software systems.
• Unit test software and perform code reviews.
• Design and implement scalable search and retrieval systems leveraging Elasticsearch.
• Develop and integrate LLM‑powered capabilities, including Retrieval‑Augmented Generation (RAG) pipelines.
• Document and track vendor software roadmaps for software and patch version updates.

• Demonstrated experience working in Lean Agile Development environment.
• Demonstrated experience translating customer and system requirements into actionable design specifications.
• Demonstrated experience designing system interfaces, including defining integration points, data flows, and data exchange workflows.
• Demonstrated experience building or integrating LLM-based solutions, including RAG pipelines, semantic search, and AI-assisted retrieval systems.
• Demonstrated experience designing and implementing data pipelines for hybrid search (BM25 + vector search) in RAG workflows, covering ingestion, chunking, embeddings, and vector retrieval.
• Demonstrated experience with Elasticsearch, included index design and optimization, query development, relevance tuning, and cluster scaling.
• Demonstrated hands‑on experience in frontend Single Page Applications (SPA) development using React (hooks), HTML5, CSS3, and modern JavaScript best practices.
• Demonstrated hands‑on experience in backend development, including designing and building RESTful APIs with Node.js and Express.js (or comparable modern backend frameworks).
• Demonstrated hands‑on experience troubleshooting web protocols and server technologies, including Apache Tomcat, Node.js, Web Services, and SSL/TLS security configurations.
• Demonstrated experience using modern testing platforms such as Jest or Karma.
• Demonstrated experience with Dev Ops tools including Git, Jenkins, and Nexus.

• Experience with the customer’s Lean Agile methodology.
• Experience evaluating, selecting, or integrating LLMs (e.g., OpenAI, open‑source models) into enterprise applications.
• Experience with vector databases, hybrid search (keyword + semantic), and relevance optimization.
• Experience with or exposure to RAG, LLM integrations, or semantic search.
• Experience with Elasticsearch or similar search platforms, with some…