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# Ai Engineer

- **Company:** AppLab Systems Inc
- **Location:** Bellevue, WA, United States
- **Experience:** Experienced
- **Salary:** $160,000
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Communications Protocols, Information Engineering, Extract Transform Load (ETL), Memory Management, Systems Integration, LangChain, Large Language Models, Multi-Agent Systems, Agentic-AI, AI Platforms, Information Technology, CrewAI, AutoGen, Model Context Protocol, Semantic Kernel, Network Server, AIOps, Agent2Agent Protocol
- **Published:** November 3, 2026
- **Apply:** https://www.thejobnetwork.com/job/4c74ef94-6527-4acc-a175-43996acd4734/ai-engineer

## About the Role

* Minimum 15 years of overall IT experience.
 * 3 years of AI/ML experience OR
 * 6 years of Data Engineering experience.

Mandatory Skills

 * Experience designing and developing Model Context Protocol (MCP) Servers and Tool Integrations.
 * Strong hands-on experience with Agentic AI frameworks:
 + LangChain
 + LangGraph
 + AutoGen
 + CrewAI
 + Semantic Kernel
 + Azure Agentic Framework
 * Expertise in designing multi-agent workflows and Agent-to-Agent (A2A) communication.
 * Experience with AIOps.
 * Experience building and managing ETL Pipelines.
 * Hands-on experience with n8n.

## Description

* Design and develop MCP servers and reusable production-grade tool integrations 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 and architect multi-agent workflows where specialized agents collaborate, delegate tasks, and share context.
 * Build and manage enterprise-scale Agentic AI solutions using LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, and Azure Agentic Framework, including orchestration, memory management, tool integration, and dynamic task routing.
 * Own the agentic platform tooling layer by designing reusable agent components, managing agent lifecycle, and ensuring reliable, observable, secure, and governed agent execution across the AI platform.