Azure AI Security Architect

Responsibilities

• Designing secure Azure cloud architectures for AI applications, data-driven platforms, and internal digital products;


• Defining architecture patterns for AI solutions consuming data from platforms such as Databricks;


• Establishing secure patterns for AI agents, sandboxed code execution, and runtime isolation;


• Designing secure network architectures including segmentation, private endpoints, and controlled access;


• Implementing standards for identity management, secrets handling, encryption, logging, and monitoring;


• Using Terraform to define and maintain reusable infrastructure-as-code patterns;


• Supporting migration from Azure DevOps to GitHub Enterprise;


• Designing and implementing modern CI/CD pipelines using GitHub Actions;


• Establishing repository governance, code review processes, and deployment controls;


• Defining secure software delivery standards with full traceability and audit readiness;


• Collaborating with engineering teams and mentoring developers in best practices across cloud, security, and DevOps.

Requirements

• Strong hands-on experience with Microsoft Azure cloud architecture


• Proven expertise in cloud security (identity, networking, encryption, secrets management, monitoring)


• Experience designing secure solutions for AI applications, APIs, or data-driven systems


• Hands-on experience with containerized workloads, Python environments, or isolated compute patterns


• Familiarity with Databricks or similar enterprise data platforms


• Strong knowledge of network security (VNETs, firewalls, private endpoints, controlled egress)


• Experience with Terraform and infrastructure as code


• Strong experience with GitHub Enterprise, GitHub Actions, and CI/CD best practices


• Experience with Azure DevOps and migration to GitHub is a strong advantage


• Knowledge of identity and access management (Microsoft Entra ID, RBAC, managed identities)


• Understanding of secure software delivery, compliance, and audit-ready engineering practices


• Ability to combine hands-on technical work with architectural leadership.

Core Competencies

Demonstrates expertise in designing secure Azure cloud architectures for AI applications and data-driven platforms, with a strong focus on cloud security, identity management, and infrastructure as code using Terraform. Proven ability to implement CI/CD best practices and mentor engineering teams in secure software delivery and compliance.

Highest-signal resume keywords

• Microsoft Azure Cloud Architecture


• Cloud Security


• Terraform


• GitHub Actions


• CI/CD Best Practices

Hard Skills

• Cloud Architecture


• AI Solutions Design


• Network Security


• Containerized Workloads


• Python EnvironmentsSecrets Management


• Identity Management


• Infrastructure as Code


• Secure Software Delivery


• Audit-Ready Engineering

Soft Skills

• Mentoring


• Collaboration

Industry Keywords

• Secure Network Architectures


• Identity and Access Management


• Compliance


• Audit Readiness


• Sandboxed Code Execution

Tools & Technologies

• Databricks


• GitHub Enterprise


• Azure DevOps