Technical Project Manager – Enterprise AI Platform

Role Summary

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:**

+ Azure Administrator / Azure Fundamentals

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.

Technical Screening Rubric

• Candidates may be assessed on the following:
• **Roadmap Design:** Develop a roadmap for hybrid AI platform rollout leveraging Azure and on-prem compute.
• **Dependency Mapping:** Identify interdependencies between cloud, data, and AI workstreams.
• **Risk Assessment:** Evaluate technical risks and define mitigation plans.
• **Azure Governance Scenario:** Design a governance model including RBAC, tagging, and policy compliance.
• **Executive Reporting:** Create a concise project update summarizing risks, health, and next steps.