Exp. Required: 10+ Year’s
Must Have Technical/Functional Skills
• Security architecture for cloud, data, and AI environments.
•
IAM, Zero Trust, encryption, secrets, secure APIs, logging, auditability, and data-loss controls.
• Experience securing sensitive datasets across IT, OT, and third-party workflows.
• Ability to work with engineering teams without disrupting delivery or platform usability.
Good to Have
Industrial cybersecurity, connected products, sensor data, OT/IT convergence, or secure MLOps.
Policy-as-code, container security, software supply-chain controls, and privacy engineering.
Roles & Responsibilities
Define security, privacy, retention, audit, and access-control architecture for multimodal data
pipelines, AI training datasets, annotation workflows, model environments, and connected
engineering platforms.
• Design identity, authentication, authorization, and privileged-access patterns for users, services,
pipelines, repositories, and machine identities.
• Define RBAC/ABAC, least-privilege, segregation-of-duties, encryption, key management, secure
transfer, and controlled data sharing.
• Translate classification, privacy, export-control, retention, and audit requirements into enforceable
controls.
• Embed security checks into CI/CD, repositories, data pipelines, containers, and model workflows.
• Create threat models, control mappings, evidence requirements, exception handling, and
remediation plans.
Managerial Skills
Work with engineering teams to embed controls without disrupting delivery or platform usability; own exception handling and remediation plans.
