Agentic AI Engineer

Booz Allen Hamilton; Washington (Washington County); Hybrid; USD 135,000 - 225,000; Full time

Benefits offered by this job

TS/SCI clearance with polygraph

Competitive benefits package

Job summary

Booz Allen Hamilton seeks an experienced Agentic AI Engineer to shift AI strategy toward proactive multi-agent orchestration. The role focuses on agent architectures, MCP/A2A protocols, and edge-optimized LLM fine-tuning using SLMs and knowledge graphs.

Candidates should have 4+ years in software, 3+ years in production ML, cloud experience (AWS/Azure), and TS/SCI clearance. The position offers a collaborative, fast-paced environment with cutting-edge AI tooling.

Qualifications

• 4+ years of software development experience.
• 3+ years building production ML solutions with Docker/Kubernetes.
• 3+ years with LangChain, LangGraph, AutoGen, PydanticAI, CrewAI, or LlamaIndex.
• 3+ years cloud experience (AWS and Azure).
• Experience with MCP for tool integration and A2A collaboration.
• Experience with RAG architectures and Knowledge Graphs (Neo4j/NebulaGraph).
• Fine-tuning LLMs/SLMs with Hugging Face, PEFT, or LoRA.
• Observation layers with Grafana, Langfuse, LangSmith, or Phoenix.
• Knowledge of microservice design or edge computing.
• TS/SCI clearance with polygraph; willingness to undergo.

Responsibilities

• Design and implement agent architectures that can reason, plan, and act.
• Develop multi-agent systems using MCP and A2A protocols for communication and tool usage.
• Build RAG pipelines integrating unstructured data with knowledge graphs to improve context.
• Fine-tune SLMs for edge deployment (ONNX/GGML/Ollama) and optimize performance.
• Develop evaluation frameworks for reliability, safety, and production readiness; include ReAct loops.

Skills

Agentic AI engineering

LangChain/LangGraph/AutoGen

LLM agents & workflows

Docker

Kubernetes

AWS/Azure cloud

MCP & A2A protocols

Knowledge Graphs (Neo4j/NebulaGraph)

Hugging Face/PEFT/LoRA

Langfuse/LangSmith/Phoenix

Edge computing / ONNX / GGML / Ollama

Grafana

TL/SCI clearance (polygraph)

Education

Bachelor's degree

Tools

Docker

Kubernetes

Neo4j

NebulaGraph

ONNX

GGML

Ollama

Hugging Face

PEFT/LoRA

Job description

Agentic AI Engineer

The Opportunity** : **

We are looking for a highly skilled Agentic AI Engineer to join our team specializing in building autonomous, goal-oriented AI systems. You will play a crucial role in shifting our AI strategy from passive LLM chatbots to proactive, multi-agent orchestrations. In this role, you will utilize deep experience in agent orchestration frameworks, RAG, knowledgegraphs, and fine-tuning Small Language Models(SLMs) for edge deployment.

What You’ll Work On:

• Design and implement intelligent agent architectures that can reason, plan, and take actions using LangChain, LangGraph, and AutoGen.
• Develop and deploy multi-agent systems using Model Context Protocol (MCP) and Agent-to-Agent(A2A) protocols to facilitate communication, tool usage, and collaborative task solving.
• Build advanced RAG pipelines integrating unstructured data with Knowledge Graphs(KG) to enhance reasoning accuracy and context retention.
• Fine-tune SLMs for specific domains and optimize them for edge device performance, including ONNX, GGML, or Ollama.
• Develop evaluation frameworks to test agent reliability, safety, and performance, moving from prototype to production, including ReAct loops and human-in-the-loop.

Join us. The world can't wait.

You Have:

• 4+ years of experience in software development
• 3+ years of experience as an ML engineer building production-grade ML solutions using tools such as Docker or Kubernetes, including, GenAI, LLMs, DL, RL, AI agents, agentic workflows, or complex automation frameworks
• 3+ years of experience with LangChain, LangGraph, AutoGen, PydanticAI, CrewAI, or LlamaIndex
• 3+ years of experience working in cloud environments, including AWS and Azure and evaluating architectural tradeoffs and designing robust service-based software applications for scalable use
• Experience with MCP for tool integration and A2A for agent-to-agent collaboration and with RAG architecture and KG, including Neo4j or NebulaGraph
• Experience fine-tuning LLMs or SLMs using Hugging Face, PEFT, or LoRA, evaluating LLM performance and behavior through evaluations, and building observation layers for stakeholders, including 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 If You Have:

• Experiencedeploying agentic systems in a production environment
• Experiencedeploying agents on edge devices such as Android or local models
• Experienceintegrating coding agents such as Cursor or Windsurf into an efficient development pipeline with measured results
• Experiencewith programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and vLLM
• Experienceengineering AI capabilities in on-premise or multi-classification environments
• Possession of excellent verbal and written communication skills for client engagements, client-facing project work, and business development
• Master's degree in a CS or AI field preferred; Doctorate degree in CS or Statistics a plus

Clearance:

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance with polygraph is required.

Compensation

At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen's benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.

Salary at Booz Allen is determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract‑specific affordability and organizational requirements. The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen's total compensation package for employees. This posting will close within 90 days from the Posting Date.

Identity Statement

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

Candidate AI Usage Policy

AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in‑person or virtual) is prohibited unless permission is explicitly provided.

Work Model

Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.

• Remote : If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.
• Hybrid : If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.
• Onsite : If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility