Lead AI Security Engineer
Mastercard1 day ago
Dublin, IrelandStaff+
Responsibilities
- Implement technical recommendations from central security and AI governance teams.
- Test AI and ML models for membership inference, model inversion, data leakage, adversarial manipulation, and related vulnerabilities.
- Build and maintain guardrails, output filters, input validation, rate limits, access restrictions, and other mitigations.
- Implement bias and fairness testing for models and AI use cases.
- Produce reproducible security and governance evidence, including test results, logs, and benchmark outputs.
- Monitor emerging model vulnerability research and attack techniques and test the platform against them.
- Partner with security, privacy, and AI governance teams as the platform’s primary technical contact.
- Advise engineers on secure API, data pipeline, and model-serving designs.
- Support incident response by reproducing findings, implementing fixes, and verifying remediation.
Requirements
- Hands-on experience testing ML/AI models for security vulnerabilities, including adversarial robustness, membership inference, model inversion, or practical model red-teaming.
- Strong applied security engineering skills with experience building technical controls, guardrails, filters, and access restrictions.
- Experience implementing bias or fairness testing or mitigation for ML models.
- Familiarity with security risks affecting embeddings and foundation models and with current attack research.
- Practical experience implementing access control and audit logging across distributed or hybrid cloud and on-premises environments.
- Working knowledge of financial and payment-data regulations such as PCI DSS and data protection regulations.
- Software engineering fundamentals and the ability to build production-quality tooling and tests.
- Clear communication skills for working with engineering and specialist advisory teams.
- Familiarity with AWS preferred; Azure or GCP are valuable, particularly in modern data and AI platforms such as Databricks.
- Ability to translate external governance and security guidance into technically correct platform implementations.
Tech Stack
Categories
About Mastercard
Mastercard builds and operates a global payments network used by banks, merchants, fintechs, and governments, offering card processing, real-time payments, tokenization, and fraud/risk services. It generates revenue from transaction processing and assessment/service fees across more than 200 countries and territories. Founded in 1966 and headquartered in Purchase, New York, Mastercard is a public company listed on the NYSE (ticker: MA).