AI Security Architect

The AI Security Architect at PayPal will be responsible for designing, evaluating and researching robust security measures for AI systems and applications. This role involves evaluating and mitigating risks associated with AI/ML models, securing data pipelines, and ensuring compliance with regulatory requirements and security standards. The ideal candidate will possess a deep understanding of both AI technologies and cybersecurity principles.

• Develop security architectures for AI systems, data, and machine learning models to ensure data protection, model integrity, and regulatory compliance.
• Conduct research and threat modeling on AI security to identify vulnerabilities, threats, and risks associated with machine learning models and data.
• Develop and maintain security standards, procedures and guidelines related to the use of AI
• Conduct security risk assessments for AI initiatives, identifying vulnerabilities in algorithms, data pipelines, and underlying infrastructure.
• Evaluate secure data workflows for AI projects, including data encryption, anonymization, and secure storage of training and inference data.
• Collaborate with AI/ML engineers, data scientists, and cybersecurity teams to integrate security controls throughout the AI development lifecycle.
• Evaluate third-party AI tools and vendors for security risks and compliance requirements.
• Implement secure coding practices for AI models and review AI algorithms for potential security risks, such as adversarial attacks or data poisoning.
• Lead the development of
• Stay updated with the latest AI and cybersecurity trends to ensure ongoing protection against new and evolving threats.
• Design novel algorithms and techniques for securing AI models and ensuring the integrity, confidentiality, and availability of AI systems.

• Ph. D or master s degree in computer science, Mathematics, Artificial Intelligence, or a related field from a top academic institution highly desired.
• Strong understanding of machine learning algorithms, data science, and AI technologies.
• Strong understanding of large language models (eg, GPT, BERT) and natural language processing (NLP) techniques
• Knowledge of cybersecurity principles, including cryptography, authentication, vulnerability assessments and threat detection.