Design and implement detection strategies that identify AI-specific threats including prompt injection, model extraction, data poisoning, adversarial examples, and unauthorized access to training datasets or model weights across our distributed infrastructure
Build automated response playbooks and orchestration workflows that contain threats without human intervention, creating self-healing security systems that reduce mean time to response from hours to minutes while automatically remediating compromised inference endpoints
Lead security incident response coordination across all teams (Cloud, AppSec, Enterprise, AI Security) when AI infrastructure or models are compromised, conducting forensic investigations on training pipeline attacks and model manipulation attempts while drafting clear incident communications for engineering and executive leadership
Hunt proactively for sophisticated threats across GPU clusters and training infrastructure by analyzing model outputs for signs of compromise, reproducing AI-specific vulnerabilities from security research, and identifying visibility gaps in distributed training environments before adversaries exploit them
Build detection-as-code frameworks with version control and automated deployment, onboard telemetry from AI training infrastructure and inference endpoints, and create dashboards that track model security metrics, GPU utilization patterns, and access to sensitive research data
Collaborate cross-functionally as the operational security partner for all teams – translating AI Security's threat research into production detections, monitoring Cloud Infrastructure's GPU clusters for threats, detecting customer-impacting incidents for Software Security Engineering, and enabling responsible AI development through security guardrails
Maintain 24/7 on-call rotation for critical AI security incidents, responding to real-time threats targeting our platform while continuously improving detection coverage and automation capabilities as our AI systems evolve