Agentic AI Engineer

Booz Allen Hamilton•Annapolis Junction, MD

1d•$99,000 - $225,000•Onsite

About The Position

As an Agentic AI Engineer, you will design, build, and deploy AI agents capable of autonomously using tools, interacting with software systems, and executing multi-step tasks. You will develop agent architectures, including decision-making logic, memory systems, and orchestration flows that enable AI agents to perform complex operations reliably and safely. You will integrate new and existing tools, define structured interfaces for agent interactions, and implement evaluation and monitoring approaches to ensure agent behavior remains predictable and aligned with mission needs. You’ll collaborate across engineering teams to deliver scalable and production-ready agentic systems that enhance capabilities across distributed environments.

Requirements

5+ years of experience designing and implementing software systems in Python
Experience creating AI agents or multi-step LLM workflows, including defining agent behavior, sequencing, or state-transition logic
Experience integrating tools, APIs, or external services into AI-driven or workflow-oriented systems
Experience building or maintaining memory systems such as session state, long-term persistence, or vector-based retrieval
Experience implementing inference request flows, including handling latency, token limits, and batching strategies
Experience writing integration tests for multi-service or multi-component systems
Knowledge of containerization and CI/CD pipelines
Knowledge of distributed system patterns such as asynchronous task handling, message routing, or service-based architectures
TS/SCI clearance with a polygraph
Bachelor’s degree in Computer Science, Engineering, or Data Science

Nice To Haves

Experience architecting multi-agent workflows, including coordination patterns such as hierarchical, collaborative, or parallel tasking
Experience implementing state machines, planners, or decision-graph logic for agent behavior and tool routing
Experience designing agent memory architectures, such as hybrid short-term/long-term memory systems or vector-based semantic recall
Experience developing evaluation, observability, and monitoring solutions for agentic systems, including traceability of decisions and tool calls
Experience with orchestration frameworks such as LangGraph, CrewAI, or AutoGen, and supporting data stores such as Redis or Postgres
Experience integrating cloud AI platforms such as AWS Bedrock AgentCore, Google Gemini Enterprise Agent Platform, or Microsoft Foundry Agent Service
Experience implementing resilience patterns such as retries with backoff, timeouts, circuit breakers, or safe-mode fallbacks for agent behavior
Experience with Docker, Kubernetes, or infrastructure-as-code tooling
Possession of excellent written and verbal communication skills

Responsibilities

Design, build, and deploy AI agents capable of autonomously using tools, interacting with software systems, and executing multi-step tasks.
Develop agent architectures, including decision-making logic, memory systems, and orchestration flows.
Integrate new and existing tools.
Define structured interfaces for agent interactions.
Implement evaluation and monitoring approaches to ensure agent behavior remains predictable and aligned with mission needs.
Collaborate across engineering teams to deliver scalable and production-ready agentic systems.