Lead Azure AI Security Engineer

We are seeking an experienced Azure AI Security Engineer to provide technical leadership in securing Azure and Microsoft cloud environments at enterprise scale. In this role, you will design and implement security architecture across cloud and hybrid environments while leveraging AI-powered tools and agentic workflows to automate and improve daily security engineering activities.

Provide technical leadership and subject matter expertise in securing Azure and Microsoft cloud environments at enterprise scale Design, implement and improve security architecture across Azure, Microsoft 365, Microsoft Entra ID, hybrid and multi-cloud environments, with Azure as the primary cloud platform Work across key cloud security domains including Cloud Security Posture Management / CNAPP / CSPM, Identity and Access Management, Privileged Access Management, Data Protection and Data Loss Prevention, Microsoft Defender security stack, SIEM/SOAR and automated incident response, Business Continuity and Disaster Recovery, DevSecOps and Infrastructure as Code security, Container, Kubernetes, API and microservice security, Compliance, governance, policy-as-code and secure cloud landing zones Plan, design and implement security controls for cloud workloads, applications, infrastructure and data Collaborate with engineering, infrastructure, development, DevOps, database, operations and compliance teams to embed security into the full delivery lifecycle Support implementation and continuous improvement of Zero Trust architecture, secure authentication, conditional access, least privilege and identity protection Develop and maintain automation scripts, workflows and security tooling using PowerShell, Python, Azure CLI, Logic Apps, Azure Functions, KQL, REST APIs and related technologies Employ AI-powered tools and agentic workflows to automate and improve daily security engineering activities such as security findings triage, log analysis, incident investigation support, configuration review, compliance evidence collection, security documentation generation, vulnerability analysis and runbook automation Design or integrate AI agents and AI-assisted automations using modern AI platforms and frameworks where appropriate, while ensuring proper security, privacy and governance controls Contribute to secure adoption of AI technologies by defining guardrails for data protection, access control, prompt security, model usage, auditability and human-in-the-loop processes Train and support other team members on cloud security practices, security processes and AI-assisted automation approaches Bachelor's degree in Computer Science, Information Security, Engineering or equivalent practical experience Hands-on experience with Microsoft Azure services and strong understanding of cloud security concepts, Azure architecture and enterprise-scale cloud environments Practical experience with Microsoft security technologies such as Microsoft Entra ID / Azure Active Directory, Microsoft Defender for Cloud and Microsoft Defender XDR Familiarity with Microsoft Sentinel, Microsoft Purview and Microsoft Intune Skills in Conditional Access, Identity Protection and Privileged Identity Management Proficiency in Key Vault, Azure Policy and Azure Monitor / Log Analytics Strong engineering background including experience with Microsoft infrastructure and cloud solutions such as Active Directory, Microsoft 365, Exchange Online and hybrid identity Security engineering experience in at least one business or technology domain, with participation in at least several production projects Understanding of software development lifecycle, DevOps/DevSecOps practices, cloud security assessment methodologies and secure-by-design principles Capability to work closely with developers, business analysts, QA engineers, architects, project managers, infrastructure and operations teams Competency to follow, maintain and improve defined security processes Practical understanding of AI-assisted productivity and automation beyond basic chatbot usage, including building or configuring AI agents, integrating LLMs with tools and APIs, prompt engineering, creating AI-assisted runbooks and using AI tools securely with awareness of sensitive data handling Good communication skills and ability to explain security risks, technical decisions and remediation plans to both technical and non-technical stakeholders Skills in scripting, automation or software development using PowerShell, Python or Bash, alongside SIEM/SOAR platforms such as Microsoft Sentinel, KQL and Logic Apps Familiarity with CNAPP/CSPM/CWPP/CIEM tools such as Prisma Cloud, Wiz or Orca, and Infrastructure as Code and policy-as-code tools such as Terraform, Bicep and Azure Policy Understanding of compliance or security frameworks such as ISO 27001, NIST or CIS Benchmarks, and container and Kubernetes security including AKS, image scanning and network policies Familiarity with AI/LLM platforms or frameworks such as Azure OpenAI, Microsoft Copilot Studio and Semantic Kernel, along with understanding of AI security risks such as data leakage, prompt injection and model governance AZ-500, SC-100, SC-200, SC-300, SC-400, AZ-104, AZ-305, CISSP, CISM, CISA, CCSP, AI-900, AI-102, PL-900