Description

• Secure AI/ML Pipelines: Design and implement robust security controls for AI/ML pipelines, ensuring the integrity and confidentiality of models and data from ingestion to deployment.
• Gemini Enterprise Security & Governance: Define, configure, and audit enterprise security baselines for Gemini Enterprise, focusing on data privacy, cloud data loss prevention (DLP), access controls, and administrative policies to prevent unauthorized data exposure.
• Threat Modeling & Assessment: Conduct threat modeling and specialized security assessments targeting AI infrastructure and large language models (LLMs), covering risks such as model theft, data poisoning, prompt injection, and unauthorized data egress.
• Adversarial Defenses: Collaborate with data science and engineering teams to operationalize adversarial ML defenses, secure agentic architectures (Agent Gateway/Registry), and deploy privacy-preserving techniques.
• Security Operations & Telemetry: Develop strategies for monitoring AI-specific security telemetry and integrating logs from Vertex AI and Gemini Enterprise into Security Command Center Enterprise (SCC-P).
• Technical Enablement: Deliver technical workshops and training on secure AI development practices to customer stakeholders.

Qualifications:
Minimum Qualifications:

• Strong background in security engineering with specialized experience in AI/ML security, including model protection and adversarial machine learning

Key Skills

Education

Bachelor's degree