AI Implementation Engineer

Key responsibilities

• Design, build, deploy, and manage AI agents using Azure AI Foundry and Copilot Studio
• Implement and configure Copilot Studio agents for business workflows, automation, and user interactions
• Leverage Azure MCP (Model Context Protocol) to enable secure context sharing, orchestration, and tool integration for AI agents
• Integrate AI agents with enterprise applications, APIs, and data sources
• Implement identity and access management (IAM) using Azure AD (Entra ID), managed identities, RBAC, and OAuth flows
• Work with Azure DevOps to:
• Create and maintain CI/CD pipelines
• Manage source control, builds, and releases
• Automate infrastructure and deployment workflows
• Develop and maintain backend logic and integrations using Python (intermediate proficiency)
• Write and optimize SQL queries for data access, analytics, and agent context enrichment
• Monitor, debug, and optimize AI agent performance, reliability, and cost
• Ensure security, compliance, and responsible AI practices are followed
• Collaborate with cross-functional teams to translate business requirements into AI-driven solutions

Maintain technical documentation and deployment guidelines