Agentic AI Engineer

Booz Allen Hamilton • Alexandria, VA

9h • $77,600 - $176,000 • Hybrid

About The Position

Booz Allen is seeking an Agentic AI Engineer to build autonomous, goal-oriented AI systems and help shift its AI strategy from passive LLM chatbots to proactive, multi-agent orchestration. The role involves designing and implementing intelligent agents that reason, plan, and take actions; developing multi-agent systems and communication protocols; building retrieval-augmented generation (RAG) pipelines that integrate unstructured data with knowledge graphs; fine-tuning small language models (SLMs) for domain-specific and edge-device use; and creating frameworks to evaluate agent reliability, safety, and performance as systems move from prototype to production.

The position is hybrid, based in Alexandria, Virginia, with an additional listed location in Annapolis Junction, Maryland. Applicants must hold a TS/SCI clearance with a polygraph and a bachelor’s degree. Booz Allen offers a projected annual compensation range of $77,600 to $176,000, along with benefits and professional development opportunities. Hybrid employees are expected to work from a Booz Allen or customer facility in accordance with leadership expectations and role needs.

Requirements

• At least 2 years of software development experience.
• At least 2 years of experience as an ML engineer building production-grade ML solutions using tools such as Docker or Kubernetes, including work involving GenAI, LLMs, deep learning, reinforcement learning, AI agents, agentic workflows, or complex automation frameworks.
• At least 2 years of experience with LangChain, LangGraph, AutoGen, PydanticAI, CrewAI, or LlamaIndex.
• At least 2 years of experience working in cloud environments, including AWS and Azure, evaluating architectural tradeoffs, and designing robust service-based software applications for scalable use.
• Experience with MCP for tool integration, A2A for agent-to-agent collaboration, and RAG architecture and knowledge graphs, including Neo4j or NebulaGraph.
• Experience fine-tuning LLMs or SLMs using Hugging Face, PEFT, or LoRA; evaluating LLM performance and behavior; and building stakeholder observation layers using Grafana, Langfuse, LangSmith, or Phoenix.
• Knowledge of modern software design patterns, including microservice design or edge computing.
• Ability to adapt in a rapidly changing environment and navigate ambiguity.
• TS/SCI clearance with a polygraph.
• Bachelor’s degree.

Nice To Haves

• Experience deploying agentic systems in a production environment.
• Experience deploying agents on edge devices such as Android or using local models.
• Experience integrating coding agents such as Cursor or Windsurf into an efficient development pipeline with measured results.
• Programming experience, including ML frameworks or tools such as TensorFlow, PyTorch, llama.cpp, and vLLM.
• Experience engineering AI capabilities in on-premise or multi-classification environments.
• Excellent verbal and written communication skills for client engagements, client-facing project work, and business development.
• A master’s degree in a computer science or AI field is preferred; a doctorate in computer science or statistics is a plus.

Responsibilities

• Design and implement intelligent agent architectures capable of reasoning, planning, and taking actions using LangChain, LangGraph, and AutoGen.
• Develop and deploy multi-agent systems using Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocols for communication, tool use, and collaborative task solving.
• Build advanced RAG pipelines that integrate unstructured data with knowledge graphs to improve reasoning accuracy and context retention.
• Fine-tune SLMs for specific domains and optimize them for edge-device performance using technologies such as ONNX, GGML, or Ollama.
• Develop evaluation frameworks for agent reliability, safety, and performance, taking systems from prototype to production and including ReAct loops and human-in-the-loop processes.

Benefits

• Health, life, and disability benefits.
• Financial and retirement benefits.
• Paid leave.
• Professional development.
• Tuition assistance.
• Work-life programs.
• Dependent care.
• Recognition awards for exceptional performance and demonstration of company values.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level