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Tier-1 employer and Bangalore location increase competition despite senior, niche AI-cloud security specialization.
Deep cloud-security, compliance, and AI-infrastructure expertise required, limiting cross-industry transferability.
Explicit 8–12 years plus required cloud security architecture and compliance experience make filters strict.
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Design and implement secure, compliant AI infrastructure platforms covering GenAI, ML pipelines, and data ecosystems across cloud-native and hybrid environments.
Lead threat modeling, risk management, and embed security-by-design and compliance-by-default principles for AI/ML systems, including Zero Trust and defense-in-depth strategies.
Oversee compliance with security frameworks (ISO 27001, SOC 2, GDPR, AI regulations), support audit readiness, develop incident response plans, and engage stakeholders for risk reporting and remediation.
8–12 years in cybersecurity architecture/cloud security with 3–5+ years in cloud-native or AI/ML environments.
Hands-on experience designing secure distributed systems and implementing Zero Trust, defense-in-depth strategies.
Expertise with cloud platforms (Azure, AWS, GCP) and security tools including IAM, encryption, SIEM, DevSecOps practices.
Certifications and regulatory exposure are preferred but not strictly mandatory; specific notice period not mentioned.
Strong background in AI/ML security architecture with practical experience integrating security into AI lifecycles and pipelines.
Experienced in managing compliance and risk in multi-cloud and regulated industry settings (BFSI, healthcare preferred).
Able to translate complex technical security risks into business and compliance outcomes for leadership and cross-functional teams.