Agentic AI & ML Software Development Engineer

Booz Allen Hamilton•Washington, DC

22h

About The Position

To achieve an organization’s mission, leaders need strong team members who can create and analyze processes, communicate requirements, and develop innovative solutions throughout the execution of the mission. Whether reviewing program-wide technical architecture or providing AI and ML expertise, our clients need someone who combines deep technical understanding of software engineering with strong architectural judgment. That is why we need you, an experienced Agentic AI & ML Software Development Engineer who can operate at a system-of-systems level to support clients in advancing AI-enabled systems within an R&D environment. As part of our team, you'll serve as a strategic technical expert for the Advanced Research Projects Agency for Health (ARPA-H), helping conceptualize, create, and execute advanced government-funded research and development programs to accelerate better health outcomes for everyone. You’ll 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 to senior ARPA-H decision makers. You’ll maintain responsibility for 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'll serve as an Agentic AI & ML Software Development Engineer advising program leadership and supporting software engineering to support the client mission. You will support clients in ensuring that program-wide technical architecture and engineering 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.