Autonomous AI Engineer — Multi-Agent Orchestrator

Booz Allen Hamilton; Bethesda (MD); On-site; USD 99,000 - 225,000; Full time

Benefits offered by this job

Health benefits

Life insurance

Disability benefits

Retirement benefits

Paid leave

Tuition assistance

Work-life programs

Dependent care

Job summary

Booz Allen Hamilton seeks an Agentic AI Engineer to design autonomous, goal-oriented AI systems and orchestrations. You will advance from passive LLM chatbots to proactive multi-agent solutions, using MCP, A2A, RAG, and knowledge graphs.

You will fine-tune Small Language Models for edge deployment and build evaluation frameworks to ensure reliability, safety, and production readiness. Strong collaboration across teams is essential.

Qualifications

• Bachelor’s degree in CS or AI.
• 5+ years ML/DS/SD experience.
• 3+ years GenAI, LLMs, and agentic workflows.
• 3+ years LangChain/LangGraph/AutoGen/LlamaIndex.
• MCP/A2A experience.
• RAG and KG experience (Neo4j/NebulaGraph).
• Fine-tuning LLMs/SLMs (Hugging Face/PEFT/LoRA).
• Knowledge of microservice or edge computing patterns.
• Ability to obtain Secret clearance.

Responsibilities

• Design intelligent agent architectures that can reason, plan, and act.
• Develop multi-agent systems using MCP and A2A protocols.
• Build RAG pipelines with Knowledge Graphs for better reasoning.
• Fine-tune SLMs for edge deployment (ONNX/GGML/Ollama).
• Develop evaluation frameworks for reliability, safety, and performance.

Skills

Machine learning

Data science

Software development

GenAI

LLMs

Agent workflows

LangChain

LangGraph

AutoGen

MCP/A2A

Education

Bachelor’s degree in CS or AI

Tools

Neo4j

NebulaGraph

ONNX

GGML

Ollama

Hugging Face

PEFT

LoRA

Job description

Booz Allen Hamilton seeks an Agentic AI Engineer to design autonomous, goal-oriented AI systems and orchestrations. You will advance from passive LLM chatbots to proactive multi-agent solutions, using MCP, A2A, RAG, and knowledge graphs.

You will fine-tune Small Language Models for edge deployment and build evaluation frameworks to ensure reliability, safety, and production readiness. Strong collaboration across teams is essential.