Manager integrating workforce management with AI transformation at TD, a major North American bank. Connecting financial, operational, and workforce planning across customer operations.
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Senior Cloud and AI Administrator
Posted last month
About the role
- Senior Cloud & AI Administrator responsible for Azure and Microsoft 365 services, implementing AI solutions. Ensuring security, scalability, modernization, and business outcomes through hands-on delivery.
Responsibilities
- The Senior Cloud & AI Administrator is responsible for building, implementing, and operating enterprise cloud and AI platforms across the organization.
- This role directly delivers Azure-based infrastructure, Microsoft 365 services, and enterprise AI solutions (including Copilot and custom AI capabilities), ensuring they are secure, scalable, and effectively utilized.
- The position actively executes across infrastructure, security, and data/AI domains to drive modernization, automation, and business outcomes through hands-on delivery and continuous optimization.
- Build and maintain enterprise platforms across:
- Microsoft Azure (IaaS, PaaS, AI services)
- Microsoft 365 and collaboration tools
- Enterprise AI ecosystem (Copilot, Azure OpenAI, AI development platforms)
- Implement cloud-first and AI-enabled solutions aligned to business needs
- Execute modernization initiatives (e.g., serverless deployments, infrastructure consolidation, automation)
- Configure, deploy, and maintain:
- Microsoft Copilot capabilities
- AI agents (Copilot Studio, Power Platform)
- AI-assisted development tools (e.g., GitHub Copilot)
- Enforce governance, privacy, and data protection controls within AI solutions
- Manage and operate:
- AI tool inventory and lifecycle
- Monitoring, usage analytics, and cost tracking
- Access controls, environment separation (Dev/Test/Prod), and publishing processes
- Implement and maintain controls with Security and Compliance teams for:
- Responsible AI usage
- Audit logging, monitoring, and investigation readiness
- Identify and remediate risks related to unsanctioned AI usage while driving adoption of approved tools
- Build, configure, and operate Azure environments, including:
- Networking and hybrid connectivity
- Identity and access (Entra ID, Conditional Access)
- Compute, storage, and data services
- Execute cloud migrations and workload placements
- Continuously optimize cost, performance, and platform reliability
- Develop and maintain automation (infrastructure as code, patching, deployment pipelines)
- Implement and enforce governance controls across cloud and AI platforms, including:
- Cost management and FinOps practices
- Access and configuration baselines
- Logging, monitoring, and incident response integration
- Execute threat modeling inputs and support risk assessments with cybersecurity teams
- Comply with all occupational safety and health rules and regulations approved by the local Country, State and Province, NFI Group management, the safety committee and Union partners
- Comply with all Environmental Management Systems certification and Occupational Safety and Health certification achieved by NFI Group
- Other duties as assigned.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, related field, or comparable industry experience
- Certifications (Preferred)
- Microsoft Certified: Azure Solutions Architect Expert
- Microsoft Certified: Azure AI Engineer Associate
- Microsoft Certified: Security, Compliance, and Identity
- TOGAF or enterprise architecture certification (nice to have)
- 8–12+ years in IT infrastructure/cloud roles
- 3–5+ years in architecture-focused positions
- Experience in enterprise-scale cloud and AI environments
- Strong expertise in:
- Microsoft Azure (compute, networking, AI services, automation)
- Microsoft 365 ecosystem (Teams, SharePoint, Copilot)
- Identity and access management (Entra ID)
- Solid understanding of:
- Enterprise AI platforms and governance models
- Data security, privacy, and compliance frameworks
- Hybrid infrastructure and networking
- Familiarity with:
- AI/ML concepts and enterprise AI deployment patterns
- DevOps / GitHub Enterprise and CI/CD pipelines (preferred)
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