Note: The job is a remote job and is open to candidates in USA. GDIT is hiring a Senior AI Software Engineer to build AI applications and agents for the operations team and end users of the cloud platform supporting the National Institute of Allergy and Infectious Diseases. The role designs, develops, and integrates LLM, RAG, document-processing, and agent solutions, and improves their performance, reliability, security, and user experience in a federal cloud environment.
Responsibilities
- Build and deploy LLM-based applications and agents, including APIs, backend services, tool calling, structured outputs, and multi-step workflows
- Build RAG and document processing pipelines covering ingestion, embeddings, vector search, and reranking
- Build evaluation into every release with test datasets, regression tests, quality metrics, and human review
- Work with platform and DevOps engineers to run solutions in production using CI/CD, containers, monitoring, and cost controls
- Work with security engineers on access control, audit logging, PII handling, approval steps for AI actions, and federal authorization (ATO) documentation
- Produce technical documentation, architecture diagrams, deployment procedures, and operational runbooks
- Advise stakeholders, communicate technical tradeoffs and recommended approaches to technical and non-technical audiences, and mentor other engineers
Skills
- Artificial Intelligence Software
- Large Language Models (LLMs)
- Machine Learning Methods
- 8 + years of related experience
- NACLC (T3)
- Bachelor's degree or equivalent experience
- 7+ years of professional software engineering, including 1+ year building LLM-based applications
- 5+ years of AI or ML application development, including 2+ years with LLMs
- At least one LLM application built and supported in production that goes beyond a simple chat interface, such as tool calling, RAG, agents, or multi-step workflows
- Experience with agent frameworks, such as LangGraph, LangChain, Strands Agents, or CrewAI
- Strong Python skills, with experience building APIs and backend services, and with Git, automated testing, and code review
- Experience with major model providers, such as OpenAI, Anthropic, Google, Azure AI, or Amazon Bedrock
- Experience deploying and debugging applications in the cloud with containers and CI/CD
- Ability to obtain and maintain a Public Trust
- LLM evaluation, tracing, and prompt versioning tools (such as LangSmith, Langfuse, or Ragas)
- Model Context Protocol (MCP) server development and integration
- AWS, including Amazon Bedrock or Bedrock AgentCore, or relevant AWS certifications (such as Solutions Architect Professional or Generative AI Developer Professional)
- Fine-tuning or customizing foundation models; knowledge bases and vector stores
- Infrastructure as code (Terraform)
- Containerized microservice architectures
- Supporting scientific research, federal government, healthcare, or similarly regulated environments
Benefits
- Medical plan options, some with Health Savings Accounts
- Dental plan options
- A vision plan
- A 401(k) plan with 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
- Paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave
- Typically 15 days of paid leave per calendar year for vacations, personal business, and illness
- An additional 10 paid holidays per year; paid leave and paid holidays are prorated based on the employee’s date of hire
- Up to 160 hours of paid leave in a rolling 12 month period through the GDIT Paid Family Leave program for eligible employees
- Short- and long-term disability benefits
- Life, accidental death and dismemberment, personal accident, critical illness, and business travel and accident insurance
Company Overview
Company H1B Sponsorship