Technical Project Manager – Enterprise AI Platform

Stellar Technologies

Abu Dhabi

On-site

AED 300,000 - 520,000

Full time

14 days+

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Job summary

Stellar Technologies in Abu Dhabi seeks an experienced Technical Project Manager to lead the delivery of an Enterprise AI Platform spanning Azure Cloud, on-prem data centers, and edge environments.

This hands-on role requires fluency in cloud platforms (Azure), AI/ML workloads, and managing cross-functional engineering teams across Infrastructure, DevSecOps, and MLOps. Strong governance and budgeting experience is essential.

Qualifications

  • 8–12 years of experience in technical project or program management, AI/ML or cloud transformation.

Responsibilities

  • Lead planning and execution of AI infrastructure and platform initiatives across Azure and hybrid environments.
  • Translate business and architecture goals into actionable project plans with milestones and KPIs.
  • Manage dependencies across infrastructure, MLOps, and DevSecOps.
  • 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.

Skills

Azure architecture
AI/ML workloads
Cross-functional leadership
CI/CD
Terraform / IaC
GPU HPC workloads
Azure DevOps / Jira
Governance & security
Azure Policy / Arc / Key Vault
Stakeholder communication

Education

Bachelor’s or Master’s in CS/Engineering

Tools

Azure DevOps Boards
Jira
Confluence
Smartsheet

Job description

Role Summary

Stellar Technologies is seeking an experienced Technical Project Manager (TPM) to lead the delivery of an Enterprise AI Platform that spans Azure Cloud, on-premises data centers, and edge environments.

This is a hands-on, delivery-focused leadership role requiring strong technical fluency in cloud platforms (especially Microsoft Azure), AI/ML workloads, and proven expertise in managing cross-functional engineering teams (Infrastructure, DevSecOps, and MLOps).

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.

Technical Screening Rubric

Candidates may be assessed on the following:

  1. Roadmap Design: Develop a roadmap for hybrid AI platform rollout leveraging Azure and on-prem compute.

  2. Dependency Mapping: Identify interdependencies between cloud, data, and AI workstreams.

  3. Risk Assessment: Evaluate technical risks and define mitigation plans.

  4. Azure Governance Scenario: Design a governance model including RBAC, tagging, and policy compliance.

  5. Executive Reporting: Create a concise project update summarizing risks, health, and next steps.

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