IAM Security & AI Architect (m/f) - Remote
Role details
Job location
Tech stack
Job description
- Review, assess, and provide feedback for AI security architecture designs with a focus on identity, authorization, and access boundaries
- Ensure IAM is secure-by-design and aligned with ECS architectures (eg, zero-trust, least privilege).
- Design IAM concepts for AI operational services
- Cloud-based AI services using SAP Business AI, SAP BTP, hyperscaler AI services
- MLOps pipelines, data platforms, and model lifecycle management
- Integrations between ECS AI services, SAP tools, and external services
- Deep understanding of technical users, service accounts, authentication mechanisms, SAML, workload identities, and token-based integrations.
- Deep understanding of tool connectors, instances, access levels and authorizations pertaining to Cloud Access Manager (CAM) and the access provisioning workflows.
- Design, configure, and govern CAM AI access controls, ensuring secure and compliant access to AI capabilities, models, services, and data
- Review and validate CAM AI access setups during security and architecture reviews, identifying gaps, risks, or misconfigurations.
Requirements
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10+ years of experience in IAM, access governance, and security architecture, ideally in complex enterprise or cloud environments.
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Identity lifecycle management
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Access provisioning and de-provisioning
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Privileged access management (PAM)
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Segregation of Duties (SoD) concepts
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AI related audit reviews in User Access Management.
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AI system components (models, agents, training, inference, data dependencies)
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Hands-on experience designing or securing AI-enabled systems (eg, AI platforms, AI services, agents, data pipelines)
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Proven experience configuring and managing AI access through CAM for AI.
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Ability to translate security architecture decisions into enforceable CAM AI access configurations, not just conceptual designs.
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Ability to write technical documentation on AI related access entitlements.
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Experience aligning CAM AI access settings with audit, compliance, and regulatory evidence requirements.
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Deep familiarity with AI-related standards and regulations, including:
- EU AI Act (risk-based AI governance)
- GDPR and privacy-by-design requirements
- Ethical AI and responsible AI principles