Responsibilities:
• Collaborate with engineering and AI/ML teams to understand pipelines and AI service security needs
• Translate requirements into automated security policies and controls
• Develop and maintain security automation scripts/tools (Python, Go, PowerShell)
• Design, implement, and oversee multi-cloud security solutions (Azure, AWS, GCP) for AI services
• Partner with vendors and internal squads to deploy and test cloud AI security services
• Stay current on cloud security trends, AI developments, vulnerabilities, and emerging threats
• Troubleshoot and resolve issues with security solutions, including root cause analysis
• Develop and deploy controls using native cloud security offerings (AWS SCP, Azure Policy, GCP Org Policies)

Requirements:
• Bachelor’s degree in Computer Science, Information Security, or equivalent experience
• Solid foundational knowledge of Cloud AI Services:
• Azure AI, Azure AI Search, Azure OpenAI, Azure AI Safety Content
• AWS Bedrock, Anthropic on AWS Bedrock
• Google Vertex AI
• Proficiency with cloud-native security & governance tools:
• Azure Policy, AWS SCP & RCP, GCP Constraints
• Experience with Infrastructure-as-Code (IaC) tools such as Terraform
• Working knowledge of Secure SDLC processes
• Familiarity with cloud-based logging and data pipeline architectures
• Proficiency in scripting languages: PowerShell, Python, Bash
• Familiarity with Policy-as-Code frameworks (Rego, OPA Policy Engine)
• Experience with CI/CD pipelines and tools:
• Azure DevOps, GitHub Actions, Jenkins
• Ability to explain complex technical concepts to non-technical stakeholders
• Familiarity with risk control frameworks and regulatory engagement
• Experience working in an Agile environment

Advantages:
• Experience securing AI/ML workloads and data pipelines in cloud environments
• Experience implementing security governance for AI Service usage
• Experience in the financial industry
• Cloud or Cyber Security certifications (e.g., Azure Security Engineer, AWS Security Specialty)