AI Engineer with Model Context Protocol (MCP)

Talent Groups; Bellevue (WA); On-site; USD 140,000 - 190,000; Full time

Job summary

Talent Groups is seeking a senior AI platform engineer to design MCP servers and integrate tools for enterprise-scale LLM agents. You will enable real-time context retrieval and action execution across enterprise APIs and data sources.

Join a team building Agentic AI frameworks with LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, and Azure Agentic Framework, focusing on orchestration, memory, and governance at scale.

Qualifications

• AI/ML experience: 3+ years or Data Engineering: 6+ years

Responsibilities

• Design and develop MCP servers and tool integrations exposing enterprise APIs, data sources, and services to LLM agents for real-time context retrieval and action execution.
• Implement Agent-to-Agent (A2A) communication protocols architecting multi-agent workflows with specialized agents that collaborate, delegate tasks, and share context for complex autonomous operations.
• Build and manage Agentic AI frameworks using LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, and Azure Agentic Framework covering agent orchestration, tool use, memory management, and dynamic task routing at enterprise scale.
• Own the agentic platform tooling layer designing reusable agent components, managing agent lifecycle, and ensuring reliable, observable, and governed agent execution across the AI platform

Skills

MCP servers design

Agent-to-Agent communication

Multi-agent workflows

Enterprise API exposure

Tools

LangChain

LangGraph

AutoGen

CrewAI

Semantic Kernel

Azure Agentic Framework

Job description

• Experience designing and developing Model Context Protocol (MCP) servers and tool integrations
• Hands-on experience with Agentic AI frameworks like LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, and Azure Agentic Framework.
• Ability to design multi-agent workflows and multi-agent communication (A2A) protocols.

AI/ML Experience - 3 Years or Data Engineering - 6 Years

Further Job Description:

• Design and develop MCP servers and tool integrations building reusable, production-grade tools that expose enterprise APIs, data sources, and services to LLM agents for real-time context retrieval and action execution.
• Implement Agent-to-Agent (A2A) communication protocols architecting multi-agent workflows where specialized agents collaborate, delegate tasks, and share context for complex autonomous operations.
• Build and manage Agentic AI frameworks using LangChain, LangGraph, AutoGen, and CrewAI , Semantic Kernel, Azure Agentic Framework covering agent orchestration, tool use, memory management, and dynamic task routing at enterprise scale.
• Own the agentic platform tooling layer designing reusable agent components, managing agent lifecycle, and ensuring reliable, observable, and governed agent execution across the AI platform