Infrastructure Engineer, AI (Microsoft)

AI Agent Development & Enablement: Design, build, and administer AI agents using Microsoft Copilot Studio, with a focus on SharePoint-based knowledge grounding. Partner directly with business users to gather requirements, co-develop solutions, and troubleshoot agent behavior, accuracy, and performance. Promote reusable design patterns and best practices for scalable agent development.

Workflow Automation (Power Platform): Develop and manage automated workflows using Power Automate and related services. Build integrations between Copilot agents and enterprise systems, ensure reliability and error handling, and optimize workflows for efficiency and maintainability. Build flows that leverage SharePoint online forms, lists, and sites.

Governance Ownership (Power Platform & Copilot): Own and enforce governance across Power Platform and Copilot Studio, including:

Environment strategy (Dev/Test/Prod).

Data Loss Prevention (DLP) policies and connector governance.

Role-based access control (RBAC) and least privilege access.

Solution lifecycle management (ALM) and deployment standards.

Data usage policies, with focus on SharePoint-based AI grounding.

Continuously refine governance to balance innovation with risk management.

Security & Risk Management: Implement and monitor security controls to protect enterprise data within AI solutions. Identify and mitigate risks such as data leakage, over-permissioning, and improper data exposure through AI agents. Partner with security teams as needed, but retain ownership of platform-level controls.

AI Integration & Targeted LLM Usage: Design and implement integrations between Microsoft Copilot and external AI platforms where appropriate. Support use of Anthropic Claude, including administration of Claude Enterprise and secure API integrations. Define when to use internal vs. external AI models.

Platform Administration: Administer Power Platform and Copilot Studio environments, including provisioning, monitoring, capacity management, and licensing optimization. Ensure platform health, performance, and alignment with enterprise standards.

Monitoring, Optimization & Reporting: Track usage, adoption, and performance of AI agents and workflows. Identify opportunities to improve accuracy, reduce cost, and increase business value. Provide reporting and insights to IT leadership and the cross-functional AI team.

User Support & Training: Provide Tier-2/3 support for AI solutions, working directly with end users to resolve issues and improve outcomes. Develop practical training materials, documentation, and governance guidelines to enable safe and effective self-service development.

Collaboration with AI Team: Work closely with a cross-functional AI team to align on priorities, standards, and emerging use cases. Contribute to enterprise AI strategy through hands-on execution and feedback from real-world deployments.