Agentic AI & ML Software Development Engineer

Booz Allen HamiltonUsa, DC

About The Position

This role is for an experienced Agentic AI & ML Software Development Engineer to support clients in advancing AI-enabled systems within an R&D environment. The individual will serve as a strategic technical expert for the Advanced Research Projects Agency for Health (ARPA-H), helping to conceptualize, create, and execute advanced government-funded research and development programs to accelerate better health outcomes for everyone. You will work with world-class scientists and engineers to support the development of high-impact solutions to society's most challenging health problems. You will leverage technical expertise to provide strategic assessments of new technologies in support of senior ARPA-H decision-makers. Responsibilities include producing and presenting findings and recommendations to a team of colleagues and clients on the feasibility and potential impact of future research programs, assisting with the management of current programs, and facilitating commercialization of successfully developed technologies. You will serve as an Agentic AI & ML Software Development Engineer advising program leadership and supporting software engineering to ensure that program-wide technical architecture and engineering adhere to rigorous AI development, evaluation, and long-term impact. Your attention to detail, flexibility, communication skills, understanding of the client's mission, and problem-solving will enable the mission's success.

Requirements

  • 7+ years of experience with software engineering, including building and operating production systems
  • Experience in high-velocity environments, including owning and shipping complex products end-to-end
  • Experience with Python and at least one other backend language such as Java, Go, or Rust
  • Experience in big tech building customer-facing AI platforms or developer tools at scale
  • Experience building and operating systems on major cloud platforms such as AWS, GCP, or Azure
  • Experience with containerization and working within CI/CD pipelines
  • Experience in prompt engineering and LLM behavior across model families
  • Experience within token economics such as cost-per-query awareness, context budget management, and prompt efficiency
  • Knowledge of modern backend frameworks and async patterns, algorithms, data structures, APIs, and software design patterns
  • Bachelor's in Computer Science or Software Engineering

Nice To Haves

  • Experience in healthcare, life sciences, or other regulated domains
  • Experience in security-conscious engineering, including input validation, output sanitization, audit logging, and responsible AI guardrails
  • Experience in startup or early-stage environments, including 0-to-1 product building, comfort with ambiguity, and a high sense of urgency
  • Experience with MCP at the client or consumer layer, including how agents discover and invoke tools via MCP
  • Ability to be a self-starter and operate within a fast-paced environment
  • Master’s degree in a relevant field

Responsibilities

  • Design and maintain core agentic systems, including reasoning, planning, memory, tool-use, and multi-agent workflows.
  • Build and evolve application-layer infrastructure such as tool-calling, MCP integration, A2A communication, and context-window management.
  • Lead LLM orchestration and RAG capabilities, including prompt design, retrieval quality, grounding, and hallucination mitigation.
  • Translate product requirements into clear technical designs and ship end-to-end features quickly and reliability.
  • Prototype and experiment with new agentic capabilities, analyze results, and iterate based on user behavior.
  • Ensure high observability and reliability through instrumentation, SLOs, guardrails, and collaboration with infrastructure engineering.
  • Uphold engineering excellence by writing high-quality code, mentoring teammates, and enforcing strong privacy, security, and compliance practices.

Benefits

  • health benefits
  • life benefits
  • disability benefits
  • financial benefits
  • retirement benefits
  • paid leave
  • professional development
  • tuition assistance
  • work-life programs
  • dependent care
  • recognition awards program
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