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Metro Bangalore location and broad AI-security plus compliance requirements increase competition.
Role requires niche AI-security and regulated-financial compliance experience, limiting cross-industry transferability.
Mandatory 7+ years and specific AI security, cloud, and regulatory expertise make filters strict.
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Own the security of integration and adoption of third-party AI and LLM services across the enterprise, focusing on secure API integrations, data protection, and governance.
Develop and maintain AI security risk frameworks aligned with regulatory requirements such as GLBA, PCI DSS, DORA, and NYDFS, including governance controls for AI adoption and shadow AI detection.
Identify and mitigate AI-specific threats like prompt injection, data leakage, and adversarial inputs, while collaborating with cross-functional teams to embed security-by-design and build detection/response capabilities.
Bachelor’s degree in Computer Science, Information Security, Engineering, or related technical field, or equivalent experience.
7+ years of experience in security engineering, application security, cloud security, or closely related discipline.
Hands-on experience securing cloud-native environments and API integrations on AWS, Azure, or GCP; strong knowledge of authentication, authorization, secrets management, and data protection.
Working knowledge of AI/ML security risks relevant to enterprise use, including prompt injection, data leakage, insecure API integrations, shadow AI, and AI supply chain risk.
Demonstrated professional focus on AI security through practical work, research, or certifications (e.g., CISSP, CCSP, CAISP, CAISS).
Experience assessing and translating technical AI security risks into actionable engineering controls and governance, especially in regulated or financial services environments.
Experienced in collaborating cross-functionally with engineering, product, and leadership teams to implement security measures for AI-enabled applications and services.