AI Engineer

SFE; Bellevue (WA); On-site; USD 96,000 - 207,000; Full time

Job summary

SFE in Bellevue, WA is seeking a contract AI Engineer to design MCP servers and tool integrations that expose enterprise APIs and data to LLM agents for real-time context retrieval and action execution. You will work with LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, and the Azure Agentic Framework to architect agent orchestration, memory management, and dynamic task routing at enterprise scale.

This onsite role (Day 1 Onsite) requires hands-on experience with multi-agent workflows and

Qualifications

• Experience designing and building MCP servers and tool integrations.
• Hands-on with Agentic AI frameworks such as LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, and Azure Agentic Framework.
• Ability to design multi-agent workflows and A2A protocols.

Responsibilities

• Design and develop MCP servers and tool integrations exposing enterprise APIs and services to LLM agents.
• Implement A2A communication protocols and architect multi-agent workflows for complex autonomous ops.
• Build and manage agent frameworks covering orchestration, memory, and dynamic routing at scale.
• Own tooling layer for reusable agent components and reliable governance of agent execution.

Skills

MCP server design

LangChain

LangGraph

AutoGen

CrewAI

Semantic Kernel

Azure Agentic

A2A protocols

Job description

Job Title: AI Engineer

Location: Bellevue (Seattle area), WA ( Day 1 Onsite)

Contract role

Required Skills:

• 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.

Good to have skills:

• AIOps knowledge.

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