Security Architect - AI

• Design secure reference architectures and patterns for AI platforms and AI applications
• Consult product, data science, and platform teams on secure AI design and implementation
• Secure AI systems against data poisoning, model theft, adversarial attacks, and other AI-specific threats
• Define and implement measures for model integrity, data privacy, bias mitigation, and robustness
• Perform threat modeling and risk reviews tailored to AI workflows and pipelines
• Implement and manage data security measures
• Ensure strong authentication and authorization (e.g. OAUTH2, RBAC, PIM) across AI services and platforms
• Design and implement secure architectures for cloud platforms (i.e. Azure, AWS, GCP)
• Guide secure use of containers, orchestration, and Infrastructure as Code (e.g. Terraform, PowerShell) for AI workloads
• Integrate requirements from ISO/IEC 27001, SOX, HIPAA, PCI DSS into AI security concepts
• Ensure alignment with ethical AI principles and evolving AI regulation, including the EU AI Act
• Define and review security concepts for AI platforms; conduct security reviews and architecture assessments
• Support incident response related to AI systems, advising on detection, containment, and remediation
• Technical leadership and collaboration with international security teams, fostering collaboration across diverse, cross-functional groups
• Act as a key link between central security, regulatory functions, and the Digital Technology Accelerator
• Contribute actively to the ZEISS-wide security community, sharing best practices in AI security

• A Master’s degree in Computer Science, Software Engineering, Electrical Engineering, Mechanical Engineering, Mathematics, or Physics
• Minimum of 7+ years of professional experience in roles such as data modeling, algorithm development, data science, or similar fields
• Proven track record in designing and implementing secure architectures for AI platforms and AI-driven use cases
• Cloud Security: Certifications or training in cloud platforms (AWS, GCP, Azure preferred) and expertise in cross-provider cloud technologies (e.g., Microsoft Azure, Google GCP, Amazon AWS, Alibaba)
• Strong understanding of software architectures, design patterns, and abstract thinking, with the ability to map capabilities to technologies effectively
• Knowledge of HSM, certificate infrastructures, key vaults, TLS protocols, and authentication methods like OAUTH2
• Expertise in securing AI platforms, addressing risks like data poisoning and model theft, and ensuring compliance with ethical AI principles, regulatory standards, and the EU AI Act
• Experience with regulatory frameworks (ISO/IEC 27001, SOX, HIPAA, PCI DSS, EU AI Act) and integrating compliance requirements into AI security strategies
• Proficiency in Python, managing code repositories, containerizing artifacts, and implementing “Infrastructure as Code” using tools like Terraform and PowerShell
• Proven ability to give technical guidance to international teams, fostering collaboration and driving security initiatives across diverse, cross-functional groups

Preferred Certifications

• AI Security Certifications (e.g., AI-specific cybersecurity certifications)
• Advanced Cloud Security Certifications (e.g., AWS Certified Security Specialty, Microsoft Certified: Azure Security Engineer Associate)