Expert AI Security Engineer

Job description

Role & responsibilities AI Security Leadership: Lead the design and implementation of security controls for AI/ML models, pipelines, and data flows. Author safety regression tests and break-glass controls. • Vulnerability Management: Ensure coverage of AI/ML and application vulnerabilities using SAST, DAST, dependency scanning, and specialized AI security tools. • Automation & Tooling: Build and maintain automation pipelines for AI/ML security testing and monitoring. • Cross-Functional Collaboration: Partner with CISO functions, Engineering, Product, and Data to embed security into AI/ML development lifecycles. • Incident Response: Support detection, triage, and remediation of AI/ML-specific security incidents. • Training & Advocacy: Facilitate secure development training focused on AI/ML risks and best practices. • Metrics & Reporting: Track and report status of vulnerabilities, including AI/ML-specific metrics (e.g., model robustness, data integrity). • Establishes routines for updating documentation, runbooks, and dashboards with AI/ML security content. • Effectively communicates complex AI/ML security topics to technical and non-technical stakeholders. Required Qualifications • 5 to 8 years in information security, with significant experience in application security and AI/ML security. • Hands-on experience securing AI/ML models, pipelines, and data within the AI/ML SDLC. Familiarity with common AI/ML security threats (adversarial attacks, model inversion, data poisoning). • Experience with security tools for AI/ML (e.g., Adversarial Robustness Toolbox). • Mandatory or scripting experience (Python preferred; experience with AI/ML frameworks a plus).