Azure InfraDevOps AI

Role & responsibilities

• It's crucial to have a deep understanding of Azure infrastructure, including Linux &

Windows.

• Design, build, and optimize Azure AI Landing Zones aligned with Microsoft Cloud

Adoption Framework (CAF) and Enterprise Scale Landing Zone architecture.

• Deploy and integrate core AI platform services including Azure OpenAI, Azure AI Foundry

/ AI Studio, Azure Machine Learning / AI work ows, Vector databases (Cosmos DB,

PostgreSQL with pgvector, Cognitive Search, Redis)

• Implement Enterprise Security for AI Landing Zones, including Private/OpenAI

endpoints, Key Vault, role-based access, identity isolation, Data loss prevention (DLP)

patterns for AI usage.

• Azure Policy guardrails and governance.
• Strong experience with Azure Landing Zones, Enterprise-scale architecture, and AI/ML

cloud infrastructure.

• Build and automate Landing Zone deployments using Terraform, or Bicep.
• Develop CI/CD pipelines for provisioning AI resources, AML pipelines, AKS clusters, and

integration patterns using Azure DevOps or GitHub Actions.

• Automate environment creation for multiple teams working on AI development.
• Strong experience with Terraform / Bicep, Azure DevOps / GitHub Actions, AKS,

Docker, and Python.

• Hands-on experience with CI/CD pipelines using Azure DevOps or GitHub Actions /

Runners

• Hands-on experience with Azure OpenAI, AI Foundry, Azure Machine Learning, and

associated ecosystem services.

• Deep understanding of Azure networking, identity, governance, and security.
• Establish secure environment patterns for prompt engineering, model deployment,

model lifecycle management, and AI agent frameworks.

• Ensure compliance with organizational and regulatory requirements when enabling

Generative AI services.

• Design Discussions and Documentation: Experience in driving design discussions with

architects and application teams, as well as documenting the processes and decisions

• Leadership and Team Management: The ability to lead a team and drive activities and

deliverables to closure as per schedule is important.

• Customer Facing Experience: Strong communication skills and experience in customer-

facing roles are required.

• Good to have - Migrate on-prem or cloud workloads to Azure AI environments