Key Responsibilities
- Lead planning and execution of large-scale AI infrastructure and platform initiatives across Azure and hybrid environments.
- Translate business and architecture goals into actionable project plans with measurable milestones and KPIs.
- Manage dependencies across infrastructure, MLOps, and DevSecOps streams.
- Oversee Agile delivery using Azure DevOps Boards or Jira (sprints, backlogs, release schedules).
- Ensure secure and efficient delivery of GPU-accelerated compute and storage workloads.
- Collaborate with architecture and engineering teams to align design, provisioning, and governance standards.
- Implement and track compliance with Azure Policy, Azure Arc, and Key Vault integrations.
- Review and validate infrastructure readiness for GPU and high-performance computing workloads.
- Maintain project governance, budgets, and progress reports using Azure Cost Management and dashboarding tools.
- Serve as the bridge between technical teams, business leadership, and vendors to ensure seamless execution.
- Coordinate licensing, resourcing, and procurement with internal finance and operations teams.
- Promote Agile and DevOps best practices, while mentoring project coordinators and engineers.
- Lead post-project retrospectives and implement process improvements for future releases.
Required Knowledge & Skills
- Strong understanding of Microsoft Azure architecture and services including Azure Machine Learning, Azure Arc, Azure Policy, and Azure Monitor.
- Experience with hybrid connectivity (VPN, ExpressRoute, private endpoints).
- Broad knowledge of AI/ML, MLOps, and DevOps delivery models.
- Familiarity with CI/CD, IaC (Terraform, Bicep), and cloud security governance.
- Hands-on exposure to GPU-based or HPC workloads.
- Deep understanding of project governance, Agile methodologies, and stakeholder communication.
- Skilled in project tools like Azure DevOps Boards, Jira, Confluence, or Smartsheet.
Experience & Certifications
- 8 12 years of experience in technical project or program management, preferably in AI/ML or cloud transformation.
- Proven success in managing cross-functional engineering projects across infrastructure, data, and platform domains.
Preferred Certifications:
- PMP / PMI-ACP
- Azure Administrator / Azure Fundamentals
- SAFe Agilist
Success Metrics (First 12 Months)
- Successful rollout of the Enterprise AI Platform across Azure and hybrid infrastructure.
- 100% of AI/ML model deployments automated via CI/CD.
- Improved deployment velocity and >99% platform availability.
- Full compliance with cost governance and resource optimization.
- Executive dashboards implemented for KPIs and risk tracking.