Agentic AI Engineer
$99,000–$225,000 year
On-siteWashington, District of Columbia, United States or McLean, Virginia, United States
Job Summary
Design and implement intelligent agent architectures that reason, plan, and take actions using LangChain, LangGraph, and AutoGen. Develop and deploy multi-agent systems via Model Context Protocol and Agent-to-Agent protocols to facilitate tool usage and collaborative task solving. Build advanced RAG pipelines integrating unstructured data with Knowledge Graphs to enhance reasoning accuracy, and fine-tune Small Language Models for edge device performance using ONNX or Ollama. Develop evaluation frameworks to test agent reliability and safety, moving from prototype to production. This role supports the strategic shift from passive chatbots to proactive, autonomous AI systems within a defense and national security technology environment.
Required Qualifications
- 5+ years of experience in machine learning, data science, or software development
- 3+ years of experience with GenAI, LLMs, and agentic workflows
- 3+ years of experience with LangChain, LangGraph, AutoGen, or LlamaIndex
- Experience with MCP for tool integration and A2A for agent-to-agent collaboration
- Experience with RAG architecture and KG, 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 CS or AI field
Desired Qualifications
- Experience deploying agentic systems in a production environment
- Experience deploying agents on edge devices such as Android or local models
- Experience integrating coding agents such as Cursor or Windsurf, into an efficient development pipeline with measured results
- Master's degree in a CS or AI field preferred
- Doctorate degree in CS or Statistics a plus
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