Agentic AI Engineer

Booz Allen Hamilton • Alexandria, VA

19d • 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 orchestrations. The role focuses on agent orchestration frameworks, retrieval-augmented generation (RAG), Knowledge Graphs (KG), and fine-tuning Small Language Models (SLMs) for edge deployment.

The engineer will design intelligent agent architectures that reason, plan, and take action; develop systems for agent communication and collaborative problem solving; build RAG pipelines that integrate unstructured data with Knowledge Graphs; and fine-tune and optimize SLMs for edge devices. The position also involves creating evaluation frameworks to assess reliability, safety, and performance as systems move from prototypes to production.

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, scalable service-based software applications.
• 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 observation layers for stakeholders using tools such as 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.
• Top Secret clearance.
• 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 with ML frameworks 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.
• Master’s degree in a computer science or AI field preferred; doctorate in computer science or statistics is a plus.

Responsibilities

• Design and implement intelligent agent architectures 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 RAG pipelines integrating 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 to test agent reliability, safety, and performance as systems progress from prototype to production, 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