KEY RESPONSIBILITIES -

- AI Security Architecture &
- Governance - Develop and implement enterprise-wide AI security strategies, standards, policies, and guardrails.
- Establish governance frameworks for AI and Generative AI solutions to ensure secure, responsible, and compliant adoption.
- Conduct AI security assessments, threat modeling, and risk evaluations for AI applications, models, and services.
- Define secure AI usage guidelines, acceptable use policies, and AI governance controls.
- Evaluate AI platforms, tools, and services from security, privacy, compliance, and operational risk perspectives.
- Design secure AI architectures, reference patterns, and security-by-design frameworks.
- Review AI solution designs and provide security recommendations throughout the project lifecycle.
- Evaluate and manage security risks associated with third-party AI vendors and cloud service providers.

- Security Architecture, Solution Design &
- Assurance - Act as the security architecture lead for AI, GenAI, and cloud transformation initiatives.
- Review and approve solution architectures to ensure alignment with enterprise security standards, policies, and regulatory requirements.
- Provide security design guidance throughout the solution lifecycle, from concept and architecture to implementation and operations.
- Conduct architecture risk assessments and identify security gaps, design weaknesses, and mitigation strategies.
- Develop and maintain reference architectures, security patterns, and reusable design frameworks for AI and cloud platforms.
- Participate in Architecture Review Boards (ARB), technical design reviews, and governance forums.
- Evaluate emerging AI technologies, cloud services, and platforms to determine security implications and architectural suitability.




- Ensure Security-by-Design and Privacy-by Design principles are embedded within AI and cloud solutions.
- Define security requirements for integrations, APIs, data flows, and third-party services.
- Collaborate with Enterprise Architecture, Cloud Engineering, Data Engineering, and Application Development teams to establish secure and scalable solutions.
- Perform security assurance reviews prior to production deployment and provide risk-based recommendations.
- Support threat modeling, attack surface analysis, and architecture assessments for strategic business initiatives.

- Cloud Security &
- Infrastructure Protection - Design and implement security controls across Azure, AWS, and GCP environments supporting AI workloads.
- Secure cloud-native AI services, machine learning platforms, data lakes, and AI development environments.
- Ensure cloud architectures comply with enterprise security standards and industry best practices.
- Implement Zero Trust Architecture principles across AI and cloud workloads.
- Integrate AI security requirements into cloud security frameworks, operating models, and engineering practices.

- Data Security &
- Privacy - Define and implement controls to protect sensitive, regulated, and business-critical data utilized by AI systems.
- Ensure data classification, encryption, tokenization, masking, and privacy-preserving controls are implemented and maintained.
- Monitor and prevent data leakage through AI applications, APIs, and cloud services.
- Establish secure data-sharing, retention,



and lifecycle management practices.
- Ensure compliance with applicable data privacy regulations and organizational data protection policies. Identity &
- Access Management - Design and implement Identity and Access Management (IAM) controls for AI platforms and cloud services.
- Enforce least-privilege access, Privileged Access Management (PAM), and solid authentication controls.
- Review access governance processes and ensure secure integration with enterprise identity platforms.

- Security Operations &
- Threat Management - Develop monitoring, detection, and response use cases for AI-specific threats, including prompt injection, model poisoning, adversarial attacks, data leakage, and unauthorized model access.
- Collaborate with SOC, Incident Response, and Threat Intelligence teams to investigate and respond to AI-related security incidents.
- Conduct vulnerability assessments, architecture reviews, and security testing activities for AI applications and supporting infrastructure.
- Support continuous monitoring and ongoing improvement of AI security controls and capabilities.

- Compliance, Risk Management &
- Awareness - Ensure compliance with ISO 27001, NIST AI Risk Management Framework (AI RMF), GDPR, HIPAA, and other applicable regulations.
- Support internal audits, external assessments, and regulatory reviews related to AI and cloud security.
- Develop and maintain AI risk registers, mitigation plans, and governance reporting mechanisms.
- Conduct AI security awareness and training programs for employees and technical teams.
- Provide guidance to development, cloud, and business teams on secure AI development and deployment practices.
- Promote responsible, ethical, and secure use of AI technologies across the organization

📌 Cloud AI Security Specialist (Bengaluru)
🏢 Biocon Biologics
📍 Bengaluru