At a glanceSummarised by Seekless from the posting.
Must have10
Master's degree in Computer Science, Software Engineering, Electrical Engineering, Mechanical Engineering, Mathematics, or Physics
Minimum of 7+ years of professional experience in 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)
Strong understanding of software architectures, design patterns, and abstract thinking
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 Terraform and PowerShell
Proven ability to give technical guidance to international teams, fostering collaboration and driving security initiatives across diverse, cross-functional groups
Nice to have2
AI Security Certifications (e.g., AI-specific cybersecurity certifications)
You will be the go‑to expert for AI security architecture, shaping how we securely design, build, and operate AI solutions across ZEISS.
Your responsibilities will include:
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Design secure reference architectures and patterns for AI platforms and AI applications
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Consult product, data science, and platform teams on secure AI design and implementation
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Secure AI systems against data poisoning, model theft, adversarial attacks, and other AI‑specific threats
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Define and implement measures for model integrity, data privacy, bias mitigation, and robustness
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Perform threat modeling and risk reviews tailored to AI workflows and pipelines
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Implement and manage data security measures
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Ensure strong authentication and authorization (e.g. OAUTH2, RBAC, PIM) across AI services and platforms
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Design and implement secure architectures for cloud platforms (i.e. Azure, AWS, GCP)
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Guide secure use of containers, orchestration, and Infrastructure as Code (e.g. Terraform, PowerShell) for AI workloads
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Integrate requirements from ISO/IEC 27001, SOX, HIPAA, PCI DSS into AI security concepts
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Ensure alignment with ethical AI principles and evolving AI regulation, including the EU AI Act
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Define and review security concepts for AI platforms; conduct security reviews and architecture assessments
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Support incident response related to AI systems, advising on detection, containment, and remediation
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Technical leadership and collaboration with international security teams, fostering collaboration across diverse, cross-functional groups
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Act as a key link between central security, regulatory functions, and the Digital Technology Accelerator
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Contribute actively to the ZEISS‑wide security community, sharing best practices in AI security
Your Profile:
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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
Nice to have
Preferred Certifications
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AI Security Certifications (e.g., AI-specific cybersecurity certifications)