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# AI Solution Architect

- **Company:** Talent Groups
- **Location:** Medina, WA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, C Sharp (Programming Language), Communications Protocols, Computer Programming, DevOps, Memory Management, Python (Programming Language), SQL Azure, Software Architecture, Role-Based Access Control, OpenAI, Cloud Services, Software Safety, Enterprise Search, Delivery Pipeline, Large Language Models, Snowflake, Multi-Agent Systems, Agentic-AI, Containerization, Kubernetes, Azure OpenAI API, AutoGen, Cosmos DB, Azure AKS, Machine Learning Operations, Cloud Integration, Azure AI, Software Coding, Semantic Kernel, Docker, Databricks
- **Published:** October 9, 2026
- **Apply:** https://www.disabledperson.com/jobs/75929319-ai-solution-architect

## About the Role

* Experience: 8+ years in software architecture, with 3+ years focused on enterprise AI and cloud solutions.
 * Azure Expertise: Deep hands-on experience with Microsoft Azure core services, Azure OpenAI, and Azure AI Foundry.
 * Frameworks: Proficiency in multi-agent frameworks like Microsoft AutoGen, Semantic Kernel, or LangChain.
 * Coding Skills: Advanced programming skills in Python or C# for agent logic and API integration.
 * MLOps: Knowledge of CI/CD pipelines, containerization (Docker, Kubernetes), and scaling LLM workloads.

## Description

* Architecture Design: Build scalable, secure, and resilient multi-agent orchestration frameworks using Azure OpenAI Service, Azure AI Agent Service, and Azure Kubernetes Service (AKS), frameworks such as Langraph and MS Agent Framework.
 * Agent Coordination: Define communication protocols, memory management, and task delegation patterns between autonomous AI agents.
 * Cloud Integration: Connect AI agents to enterprise data sources via Azure Cosmos DB, Azure AI Search, and Azure SQL, Snowflake , Databricks.
 * Security & Governance: Implement AI safety guardrails, role-based access control (RBAC), and monitoring using Azure AI Content Safety and Azure Monitor.
 * Collaboration: Guide software engineers, data scientists, and DevOps teams through implementation and deployment.
 * Evaluation of AI Agents: evaluation of agents/LLMs (responses accuracy, consistency, hallucinations, etc).