Job Description: M365 Copilot Engineer - Enterprise AI & Agent Ecosystem

• Designs, builds, deploys, and maintains enterprise integration of Microsoft 365 Copilot services (Copilot for Work/Web, Copilot Studio, Copilot for Azure, Security Copilot, etc.) into client's IT infrastructure. Ensures these AI-powered systems function efficiently, securely, and seamlessly alongside existing technology. Applies in-depth experience with cloud and on-premises infrastructure to plan and coordinate the rollout of Copilot solutions, with robust security controls and disaster recovery options in place.
• Develops and tests connectors for internal tools and data sources to extend Copilot capabilities; vets new Copilot and agentic features/integrations in a controlled environment before enterprise rollout, ensuring they meet security and performance standards.
• Manages Copilot Studio access and coordinates proof-of-concept (PoC) activities for emerging Copilot technologies, collecting feedback and refining solutions prior to broad deployment.
• Ensures endpoint readiness (e.g. verifies Netskope configurations, Windows 11 compatibility, 64-bit Office support) so that user devices and networks can fully support Copilot features.
• Collaborates with enterprise architecture and risk teams (ARC) and engineering on secure vetting of Azure Copilot and Security Copilot features, validating compatibility and compliance with client's requirements for deployment.
• Researches and acts on Azure Advisor recommendations to improve cloud performance, reduce costs, and enhance security posture; proposes actionable improvements to optimize Copilot services based on these insights.
• Develops and leverages AI-driven automation tools (e.g. an AI "shell" using Azure CLI) to create internal solutions that streamline Azure operations and support Client's cloud automation initiatives.
• Monitors and manages the security posture of Copilot services, proactively preventing policy conflicts and mitigating risks associated with integrating new AI capabilities into the environment.
• Identifies performance-impacting policies or configurations and suggests enhancements to improve system efficiency and user experience for Copilot-enabled services.
• Acts as the primary technical liaison between the Copilot integration team and other IT teams, vendors, and partners - collaborating to design solutions and resolve complex issues related to Copilot and M365 services.
• Diagnoses complex issues across network, cloud, or application layers (e.g. latency, integration errors) and implements corrective solutions to ensure high availability of Copilot features.
• Manages and coordinates the release of Copilot-related changes into production, following standardized change management procedures to minimize risk to existing services.
• Creates release plans, test and validation strategies, and schedules/tracking tools to ensure smooth deployment of Copilot updates and new integrations with minimal disruption.
• Evaluates the effectiveness of current systems and integration approaches, and assists in developing improvement strategies for Copilot and related services based on findings.

Qualifications Foundational

• Network routing, switching, and security
• Configuration management
• Systems administration
• Scripting languages (e.g. PowerShell, Python)
• IT infrastructure library (ITIL) basics
• Root cause analysis and troubleshooting
• Cloud computing fundamentals
• Cybersecurity and privacy principles
• IT automation mindset (Digital First)
• Building and managing relationships
• Adaptability and continuous learning

Intermediate

• Network routing, switching, and security (intermediate proficiency)
• Virtualization and virtual machines
• Operating systems & platforms (Windows/Linux)
• Microsoft 365 and Azure cloud platform administration
• Infrastructure as Code (IaC) practices
• Quality assurance and control processes
• Identity and access management (e.g. Azure AD/Entra ID)
• Containerization (e.g. Docker, Kubernetes)
• Continuous improvement management

Advanced

• Hardware infrastructure (advanced knowledge)
• Version control systems (e.g. Git)
• Enterprise cloud architecture & SaaS integration
• Experience with AI/ML-powered solutions and automation

Experience Typically 5-7 years of relevant experience in IT infrastructure, cloud services, or software engineering (or an equivalent combination of education and experience). A post-secondary degree in a related field of study is preferred. Deep knowledge and technical proficiency are gained through extensive hands-on experience and continuous learning in fast-evolving technology environments.