Senior AI Software Engineer

General Dynamics Information Technology•Sterling, VA
•$128,039 - $173,229•Onsite

About The Position

GDIT is seeking a highly motivated and experienced Senior AI Software Engineer to support the development, modernization, integration, and sustainment of our on-premises, AI-powered enterprise chatbot platform supporting the U.S. Department of State in Sterling, VA. The selected candidate will design, develop, and integrate software solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, document processing technologies, and modern AI inference frameworks. This role requires a strong foundation in software engineering, Python development, API integration, containerization, and AI application architecture. The engineer will help transition existing AI services toward a scalable, containerized architecture while introducing new capabilities that enhance system performance, reliability, security, and user experience. The ideal candidate is a hands-on software engineer who can work across the AI application stack, from backend development and model serving integration to data processing, automated testing, and deployment. The individual will collaborate with AI/ML engineers, data engineers, infrastructure specialists, cybersecurity teams, and government stakeholders to deliver secure, reliable AI capabilities in highly controlled, classified, and air-gapped environments.

Requirements

  • Minimum Secret Clearance, no sponsorship
  • Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Computer Engineering, or a related technical field, or equivalent practical experience.
  • 5+ years of professional software engineering experience, including backend application development.
  • Strong proficiency in Python and experience developing production-quality software.
  • Experience developing RESTful APIs and integrating distributed application services.
  • Hands-on experience integrating LLMs or generative AI capabilities into software applications.
  • Understanding of transformer-based models, inference APIs, prompt engineering, and LLM application development.
  • Experience with RAG concepts, including document ingestion, embeddings, vector search, and retrieval pipelines.
  • Experience working with relational databases such as PostgreSQL.
  • Familiarity with container technologies such as Podman or Docker.
  • Experience with Linux-based development and application deployment.
  • Proficiency with Git, automated testing, debugging, and software development best practices.
  • Experience troubleshooting applications across multiple interconnected services.
  • Strong analytical, problem-solving, communication, and technical documentation skills.
  • Ability to work effectively with cross-functional teams and government stakeholders.

Nice To Haves

  • Experience with OpenWebUI, including configuration, integration, custom Functions, Tools, or application extensions.
  • Hands-on experience with vLLM, Ollama, Hugging Face Transformers, or other LLM inference technologies.
  • Experience serving or integrating open-weight LLMs in on-premises environments.
  • Experience with NVIDIA GPUs, CUDA, GPU memory management, and AI inference optimization.
  • Experience with PostgreSQL pgvector, vector similarity search, and semantic retrieval.
  • Familiarity with embedding models, rerankers, and cross-encoder architectures.
  • Experience with Docling, Tesseract, or document intelligence technologies.
  • Experience implementing production RAG pipelines and evaluation frameworks.
  • Familiarity with agentic AI frameworks, tool calling, and Model Context Protocol (MCP).
  • Experience developing or maintaining containerized microservice architectures.
  • Familiarity with Redis, PgBouncer, and asynchronous background processing.
  • Experience with Red Hat Enterprise Linux and Windows Server.
  • Experience with FastAPI, Pydantic, pytest, and related Python technologies.
  • Experience using Splunk for application monitoring and troubleshooting.
  • Familiarity with software supply chain security, vulnerability scanning, and container hardening.
  • Experience supporting federal government systems, classified networks, or air-gapped deployments.
  • Knowledge of federal cybersecurity requirements, RMF, and ATO processes.

Responsibilities

  • Design, develop, test, and maintain Python-based applications, microservices, and APIs supporting an on prem chatbot.
  • Extend, configure, and integrate OpenWebUI with enterprise AI services and backend systems.
  • Develop custom OpenWebUI Functions, Tools, and integrations to support mission-specific use cases.
  • Integrate approved LLMs into chatbot using OpenAI-compatible APIs and inference frameworks such as vLLM and Ollama.
  • Develop reusable software components for AI model access, prompt management, response processing, and application workflows.
  • Collaborate with AI/ML engineers to improve model inference performance, response quality, and application reliability.
  • Support multimodal AI use cases, including document understanding, optical character recognition, and vision-language model integration.
  • Develop backend capabilities to support secure enterprise AI workflows.
  • Design, implement, and optimize RAG workflows for enterprise document search and question answering.
  • Integrate document processing technologies such as Docling, Tesseract, and vision-language models into automated ingestion pipelines.
  • Develop document chunking, metadata extraction, embedding generation, and retrieval workflows.
  • Integrate embedding models and reranking models to improve retrieval accuracy and relevance.
  • Work with PostgreSQL and pgvector to support vector search, semantic retrieval, and document indexing.
  • Develop APIs and background processing services for document ingestion and knowledge base management.
  • Collaborate with data engineers to ensure accurate storage, indexing, and retrieval of enterprise information.
  • Implement testing and evaluation approaches to measure RAG accuracy, retrieval relevance, and answer quality.
  • Integrate and maintain AI inference services using vLLM, Ollama, and compatible model-serving frameworks.
  • Support the deployment and configuration of approved open-weight LLMs, embedding models, rerankers, and vision-language models.
  • Develop software integrations using OpenAI-compatible REST APIs.
  • Assist in optimizing inference configurations, including context length, GPU memory utilization, concurrency, and model serving performance.
  • Support the transition from existing inference frameworks to improved architectures as technologies mature.
  • Collaborate with AI/ML engineers to troubleshoot inference errors, model loading issues, and integration failures.
  • Develop benchmarking and performance-testing utilities for AI workloads.
  • Support the migration of DS Chat components from traditional deployments into containerized services.
  • Develop, configure, and maintain container images using Podman or Docker.
  • Create and maintain Podman Compose configurations defining application services, networking, volumes, and environment variables.
  • Integrate services such as OpenWebUI, vLLM, Docling, PostgreSQL, pgvector, PgBouncer, and Redis.
  • Develop scripts and automation for repeatable installation, deployment, upgrades, and recovery.
  • Implement health checks, readiness checks, logging, and service dependency management.
  • Troubleshoot container networking, authentication, storage, GPU access, and service connectivity.
  • Collaborate with infrastructure and cybersecurity teams to improve deployment consistency and security.
  • Research, prototype, and develop agentic AI capabilities for future DS Chat releases.
  • Implement controlled tool-calling and multi-step AI workflows.
  • Develop integrations that allow approved AI models to interact with authorized enterprise APIs and services.
  • Explore emerging technologies involving AI orchestration, workflow automation, and Model Context Protocol (MCP).
  • Design secure execution boundaries, permissions, audit logging, and approval mechanisms for AI-driven actions.
  • Collaborate with stakeholders to evaluate new AI capabilities for mission relevance, security, and operational feasibility.
  • Implement safeguards to support human oversight and prevent unauthorized actions by AI-enabled systems.
  • Apply software engineering best practices, including modular architecture, code reviews, documentation, and version control.
  • Develop automated unit, integration, regression, and performance tests using frameworks such as pytest.
  • Build integration tests validating communication between OpenWebUI, inference services, document processing components, and databases.
  • Support CI/CD processes appropriate for disconnected and classified environments.
  • Troubleshoot production issues through application logs, metrics, traces, and system diagnostics.
  • Integrate operational logging and monitoring capabilities with tools such as Splunk.
  • Assist with vulnerability remediation, dependency management, software supply chain reviews, and container security assessments.
  • Produce technical documentation, deployment procedures, architecture diagrams, and operational runbooks.
  • Participate in Agile development activities, including sprint planning, technical design reviews, and demonstrations.
  • Design software solutions suitable for secure, on-premises, air-gapped government environments.
  • Implement secure authentication integration, role-based access controls, API authorization, and data protection measures.
  • Ensure AI services communicate only through authorized internal network paths.
  • Support software packaging and offline deployment using preapproved dependencies, container images, and model artifacts.
  • Collaborate with cybersecurity personnel to address security findings and support Risk Management Framework (RMF) activities.
  • Assist with technical documentation and evidence required for TRB/CCB reviews and Authority to Operate (ATO) processes.
  • Follow approved procedures for handling sensitive and classified information.

Benefits

  • Variety of medical plan options, some with Health Savings Accounts
  • Dental plan options
  • Vision plan
  • 401(k) plan offering the ability to contribute both pre and post-tax dollars up to the IRS annual limits and receive a company match.
  • Full flex work weeks where possible
  • Variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave.
  • Short and long-term disability benefits
  • Life insurance
  • Accidental death and dismemberment insurance
  • Personal accident insurance
  • Critical illness insurance
  • Business travel and accident insurance
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service