Security Architect - AI (f/m/x)

Step out of your comfort zone, excel and redefine the limits of what is possible. That's just what our employees are doing every single day – in order to set the pace through our innovations and enable outstanding achievements. After all, behind every successful company are many great fascinating people.

In a spacious modern setting full of opportunities for further development, ZEISS employees work in a place where expert knowledge and team spirit reign supreme. All of this is supported by a special ownership structure and the long-term goal of the Carl Zeiss Foundation: to bring science and society into the future together.

Join us today. Inspire people tomorrow.

Diversity is a part of ZEISS. We look forward to receiving your application silence of gender, nationality, ethnic and social origin, religion, philosophy of life, disability, age, sexual orientation or identity.

Apply now! It takes less than 10 minutes.

Your Role:

You will be the go‐to expert for AI security architecture, shaping how we secure design, build, and operate AI solutions across ZEISS.

Your responsibilities include:

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 active 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 skills to effectively

Knowledge of HSM, certificate infrastructures, key vaults, TLS protocols, and authentication methods like OAUTH2

Expertise in 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)