AI Engineer

EEOC

. Design and implement intelligent agent architectures that can reason, plan, and take actions using LangChain, LangGraph, and AutoGen .

Posted 5/7/2026full-timeWashington, DC • District of Columbia, Maryland, Washington • 🇺🇸 United StatesMid-LevelSenior💰 $99,000 - $225,000 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudDockerGrafanaKubernetesNeo4jReactTypeScript

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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
TS/SCI clearance with a polygraph
Bachelor’s degree

Benefits

Comp & perks

health, life, disability, financial, and retirement benefits
paid leave
professional development
tuition assistance
work-life programs
dependent care
recognition awards program for exceptional performance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

LangChainLangGraphAutoGenModel Context Protocol (MCP)Agent-to-Agent (A2A)RAG pipelinesKnowledge Graphs (KG)SLMsONNXHugging Face

Soft Skills

collaborative task solvingcommunicationevaluation frameworksreliability testingsafety assessmentperformance optimization

Certifications

TS/SCI clearance with polygraph