Delivery Project Lead

Job Title: Security Architect - AI Products & Multi-Cloud Security

Location

:

Offshore(

Bangalore/Pune/Hyderabad)

Job Summary

Security Architect

Key Responsibilities

• Application Security:
• Develop security policies and practices for AI and ML models.
• Conduct security assessments, code reviews, and threat modeling for AI applications.
• Implement security measures following OWASP Top 10 guidelines to prevent common vulnerabilities.
• DevSecOps:
• Integrate security into CI/CD pipelines to enable automated security testing.
• Use tools like GitHub Actions, Jenkins, and Terraform to automate infrastructure security checks.
• Promote secure coding standards and practices across development teams.
• Data Security:
• Design and implement data protection mechanisms such as encryption (both at rest and in transit) and data anonymization techniques.
• Ensure compliance with data privacy regulations such as GDPR and CCPA.
• Utilize tools like Data Loss Prevention (DLP) and data masking technologies for sensitive data protection.
• Identity & Access Management (IAM):
• Develop and enforce IAM strategies across multi-cloud platforms (AWS, Azure, GCP).
• Implement Zero Trust Architecture and role-based access controls (RBAC) to safeguard user access.
• Utilize multi-factor authentication (MFA) and identity federation protocols.
• AI Security & AI Guardrails:
• Define AI guardrails to mitigate risks like model drift, bias, adversarial attacks, and unauthorized model access.
• Implement AI model monitoring tools like LIME, SHAP, and IBM AIF360 for model interpretability and fairness.
• Promote Responsible AI practices, ensuring ethical AI deployment and compliance with industry standards.
• Cloud Security:
• Architect and implement secure cloud environments using AWS, Azure, and GCP services.
• Leverage cloud-native security tools such as AWS Shield, Azure Security Center, and Google Security Command Center.
• Conduct regular cloud security audits and vulnerability assessments.
• Compliance & Governance:
• Ensure alignment with security and compliance frameworks like NIST, ISO 27001, and SOC 2.
• Lead security audits and penetration testing to identify and mitigate vulnerabilities.
• Establish security policies and guidelines to ensure organizational compliance.
  

Technical Skills Required

• 3+ years of experience in Data Privacy, cybersecurity, focusing on AI and cloud security.
• Hands-on experience with one major cloud (AWS, Azure, or GCP) or preferably multi-cloud security (AWS, Azure, GCP) and AI model governance.
• Strong knowledge of DevSecOps practices and automated security testing.
• Proficiency with AI/ML security frameworks and tools for monitoring and securing AI models.
• Experience with security tools like Burp Suite, OWASP ZAP, and SonarQube.
• Familiarity with AI ethics, model explainability tools (e.g., LIME, SHAP), and AI risk management.
• Strong understanding of Privacy by Design Principle, data privacy regulations (GDPR, CCPA) and data security best practices.
• Knowledge of identity management solutions and best practices in IAM.
• Strong knowledge of Data lifecycle management in AI context.
  

Preferred Qualifications

• Certified Information Systems Security Professional (CISSP)
• Certified Cloud Security Professional (CCSP)
• AWS Certified Security - Specialty
• Azure Security Engineer Associate
• Certified AI Ethics & Governance Professional
  

Soft Skills

• Excellent communication skills to collaborate with cross-functional teams, including Data Science, DevOps, and Product Management.
• Strong analytical and problem-solving abilities.
• Proven ability to stay updated with the latest security trends, AI regulations, and cloud technologies.
• Ability to articulate security concepts and practices to both technical and non-technical stakeholders.
  

Nice-to-Have

• Experience with Machine Learning Operations (MLOps) security.
• Hands-on knowledge of Container Security (Docker, Kubernetes).
• Familiarity with AI ethics frameworks and AI safety research.
• Exposure to Responsible AI tools and methodologies.