Senior AI Security Engineer

Design and implement security controls and architectures for AI/ML and generative AI systems across the full lifecycle (data through monitoring).

Perform AI/ML threat modeling, adversarial testing, and AI red teaming to identify and mitigate AI-specific security risks.

Integrate AI security measures into ML delivery pipelines, monitoring systems, and incident response workflows collaborating with cross-functional teams.

Bachelor’s degree in Computer Science, Cybersecurity, Engineering, Data Science, or related field (or equivalent experience).

5+ years of experience in security engineering, application/product security, cloud security, or DevSecOps.

2+ years of experience securing AI/ML systems (including LLM-based applications) in production environments.

Strong knowledge of AI/ML security risks (prompt injection, data poisoning, model extraction, etc.) and experience with CI/CD and ML pipeline security on cloud platforms (AWS, Azure).

Proven ability to lead AI security architecture and threat modeling with practical implementation experience in complex, production AI/ML environments.

Experience bridging security with engineering, data science, and DevSecOps teams to embed AI security throughout product lifecycles and operations.

Strong understanding of AI-specific frameworks such as OWASP Top 10 for LLM Applications, MITRE ATLAS, and NIST AI Risk Management Framework for aligning security efforts to industry standards.