About this role
Booz Allen Hamilton seeks an AL/ML Technical Lead to set the technical direction for mission-critical AI systems supporting public health and safety. The hybrid position is listed in Atlanta, Georgia, with Washington, DC, as an additional location. The lead will guide engineers and work with data engineers, architects, product owners, and stakeholders on enterprise AI strategy, architecture standards, and delivery.
Responsibilities
- Design and deliver scalable AI/ML and generative AI systems, including AI agents, retrieval-augmented generation (RAG) pipelines, and MCP-enabled workflows. Lead end-to-end design across data pipelines, modeling, retrieval, agent orchestration, memory and state management, and production deployment.
- Develop systems using PySpark and Palantir Foundry; integrate tools such as Prompt Buddy, Codex, Claude, and OpenEvidence into enterprise workflows.
- Define evaluation approaches for performance benchmarking, retrieval optimization, safety validation, and production monitoring. Establish governance, privacy, anonymization, documentation, and ethical AI practices so systems are performant, explainable, secure, and appropriate for public health data.
Required qualifications
- 5+ years designing, developing, and deploying AI/ML solutions using Python; 5+ years with generative AI, LLMs, AI agents, or RAG in enterprise environments; and 3+ years with AI agents, MCP frameworks, or AI evaluation strategy development.
- Experience with TensorFlow or PyTorch for production models; PySpark, SQL, Palantir Foundry and Foundry AIP for data engineering; technical team management; MLflow and Azure or Databricks; and enterprise AI tools such as Codex, Claude, Prompt Buddy, or OpenEvidence.
- Knowledge of public health, healthcare, or government data systems and governance; a bachelor's degree; and ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements. Selected applicants are subject to a government investigation.
Preferred qualifications include healthcare, biomedical, or government public health AI/ML experience; open-source LLMs such as LLaMA, Gemma, or Phi; conversational AI or full-stack AI applications; containerization, CI/CD, orchestration, production MLOps, Agile and Jira; technical documentation and architecture presentations; enterprise AI governance; retrieval, ranking, and decision-support systems; and a relevant master's degree. The projected annual compensation range is $128,700.00–$292,000.00.