Generative AI Developer designing, building, and deploying AI applications on AWS. Collaboration with platform, data, and product teams to deliver secure and scalable solutions.
About the role
- Agentic AI Engineer specializing in building autonomous, goal-oriented AI systems at Booz Allen Hamilton. Transitioning AI strategy from LLM chatbots to proactive multi-agent orchestrations.
Responsibilities
- 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 MCP (Model Context Protocol) and A2A (Agent-to-Agent) 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 Small Language Models (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.
Requirements
- 5+ years of experience in software development
- 2+ years of experience with GenAI, LLMs, and agentic workflows
- Experience with LangChain, LangGraph, AutoGen, or LlamaIndex
- Experience with Model Context Protocol (MCP) for tool integration and A2A for agent-to-agent collaboration
- Experience in RAG architecture and Knowledge Graphs, including Neo4j or NebulaGraph
- Experience fine-tuning LLMs or SLMs using Hugging Face, PEFT, or LoRA
- Knowledge of modern software design patterns, including microservice design or edge computing
- Ability to obtain a Secret clearance
- Bachelor’s degree in a Computer Science or AI field
Benefits
- health, life, disability, financial, and retirement benefits
- paid leave
- professional development
- tuition assistance
- work-life programs
- dependent care
- recognition awards for exceptional performance
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