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Niche Azure Generative AI security specialization reduces applicant pool despite metro location.
Highly domain-specific Azure and Generative AI security expertise limits cross-industry transferability.
Explicit 7–8 years requirement and mandatory Azure security and DevSecOps skills create strict filters.
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Own end-to-end security architecture and implementation for enterprise Generative AI solutions on Microsoft Azure.
Lead protection of AI systems against specialized threats (prompt injection, jailbreaks, model inversion, data leakage) and secure AI components like RAG pipelines, vector databases, and inference endpoints.
Implement and maintain Azure cloud security (including Azure OpenAI, AKS, Defender for Cloud, Sentinel) and DevSecOps practices with CI/CD pipeline security, vulnerability assessments, and continuous monitoring.
7-8 years experience in Security Engineering, DevSecOps, or Cloud Security with minimum 2 years in securing enterprise Generative AI applications.
Advanced hands-on expertise with Azure OpenAI, Azure AI Foundry, AKS, Azure DevOps, Entra ID, Microsoft Defender for Cloud, Sentinel, WAF, NSGs, Private Link.
Strong familiarity with security frameworks OWASP Top 10, OWASP LLM Top 10, MITRE ATLAS, and NIST AI RMF.
Proficiency in scripting (Python, PowerShell, or Bash) and infrastructure as code tools like Terraform or Bicep.
Technically independent leader capable of designing and managing complex cloud security infrastructures for AI deployments.
Specialized in securing AI models and systems, particularly with knowledge of emerging AI-specific threats and mitigation.
Experienced in embedding security throughout the software development lifecycle in a cloud-native Azure environment with strong DevSecOps collaboration.