Agentic AI Engineer

Booz Allen Hamilton

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Alexandria, VAAnnapolis Junction, MD
Salary: $77,600–$176,000 / yr
Employment: Full-time
Posted: 53 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $204k

This role $127k

$57k $274k

below market most similar roles pay here above market

This role pays less than 92% of similar roles. Most pay $162,000–$246,150 — the blue band above. At the midpoint, this role pays about $127k versus about $204k for comparable roles.

Based on 240 similar postings.

Employer

About Booz Allen Hamilton

Booz Allen Hamilton is a management and technology consulting firm that provides analytics, digital, engineering, and cybersecurity solutions primarily to U.S. government agencies and commercial clients. Industry: Management & Technology Consulting

Booz Allen Hamilton currently has 1781 open roles on FindRole.

Listed pay typically runs $86,800–$198,000 across 898 roles with salary data.

Most-posted roles

View all roles at Booz Allen Hamilton

At a glance

TL;DR · Agentic AI Engineer

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The Agentic AI Engineer joins a team focused on building autonomous, goal-oriented AI systems, shifting strategy from passive chatbots to proactive multi-agent orchestrations. You will design and implement intelligent agent architectures capable of reasoning and planning while developing multi-agent systems using Model Context Protocol and Agent-to-Agent protocols. Key responsibilities include building advanced RAG pipelines integrating unstructured data with Knowledge Graphs, fine-tuning Small Language Models for edge deployment, and developing evaluation frameworks for reliability and safety. You will utilize technologies including LangChain, LangGraph, AutoGen, PydanticAI, CrewAI, LlamaIndex, Docker, Kubernetes, AWS, and Azure. Core skills involve using Hugging Face, PEFT, LoRA, Neo4j, and NebulaGraph to solve complex automation problems, while optimizing models for ONNX, GGML, or Ollama in production environments.

Skills

LangChain LangGraph AutoGen RAG Knowledge Graphs Fine-tuning ONNX GGML Ollama Docker Kubernetes AWS Azure PydanticAI CrewAI LlamaIndex Neo4j NebulaGraph Hugging Face PEFT LoRA Grafana Langfuse LangSmith Phoenix TensorFlow PyTorch llama.cpp vLLM Edge Computing

What you'll do

Design and implement intelligent agent architectures using LangChain, LangGraph, and AutoGen.
Develop multi-agent systems using Model Context Protocol and Agent-to-Agent protocols.
Build advanced RAG pipelines integrating unstructured data with Knowledge Graphs.
Fine-tune Small Language Models for specific domains and optimize them for edge deployment.
Develop evaluation frameworks to test agent reliability, safety, and performance.
Implement ReAct loops and human-in-the-loop systems for production-grade AI solutions.

What we're looking for

TS/SCI clearance with a polygraph.
2+ years of experience in software development.
2+ years of experience as an ML engineer building production-grade ML solutions using tools such as Docker or Kubernetes.
2+ years of experience with LangChain, LangGraph, AutoGen, PydanticAI, CrewAI, or LlamaIndex.
2+ years of experience working in cloud environments, including AWS and Azure.
Experience with MCP for tool integration, A2A for agent-to-agent collaboration, and RAG architecture with Knowledge Graphs like Neo4j or NebulaGraph.
Experience fine-tuning LLMs or SLMs using Hugging Face, PEFT, or LoRA, and building observation layers like Grafana, Langfuse, LangSmith, or Phoenix.
Bachelor’s degree.

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