Overview
Responsible for designing, deploying, and monitoring AI systems that adhere to organizational policies and global best practices, including managing data security posture, securing AI/ML data pipelines, and enhancing cloud security.
Key Responsibilities
- Oversee organizational AI platforms for development, testing, and production environments.
- Implement best practices for AI lifecycle management, including model deployment, monitoring, and retirement.
- Review AI applications to ensure compliance with organizational policies, ethical AI principles, and regulatory requirements.
- Lead risk assessments and mitigation strategies for AI/ML systems and sensitive data.
- Contribute to threat-modeling and incident response planning for AI-related risks.
- Establish and maintain data lineage tracking for AI models to ensure transparency and compliance.
- Collaborate with data scientists, developers, and compliance teams to enforce secure data governance.
- Design and implement automated DSPM workflows using Microsoft Purview and Azure-native tools.
- Develop and maintain security automation scripts and integrations (e.g., PowerShell, Python, Logic Apps).
- Monitor and optimize Azure security controls including Defender for Cloud, Sentinel, and Key Vault.
- Ensure proper configuration of identity and access management for AI workloads.
- Stay updated on emerging AI security trends, frameworks, and regulatory changes.
- Advise leadership on strategic AI security initiatives and risk posture improvements.
- Act as a main point of reference to support staff of all levels in understanding current practices and systems.
- Work actively towards the achievement of IFRC’s goals.
- Abide by and work in accordance with the Red Cross and Red Crescent principles.
- Perform any other work-related duties and responsibilities that may be assigned by the line manager.
Required Experience
- 7+ years of experience in AI/ML development and deployment.
- 5+ years in cloud security and data governance roles, preferably in large-scale or global organizations.
- Demonstrated experience in implementing AI security frameworks and compliance standards.
- Expertise in AI model lifecycle management and MLOps.
- Experience with generative AI, large language models (LLMs), and prompt engineering.
- Preferred Experience with Microsoft Azure environments and Microsoft Purview.
- Preferred Familiarity with agile development practices and iterative model improvement.
Qualifications
- Degree in computer science, information security, data science, or related field.
- Certifications for Azure Security Engineer, Certified Information Systems Security Professional – CISSP or similar (highly desirable).
