Lead Zeta’s AI-native Application Security function by defining strategy, building the team, embedding security agents and policy-as-code into IDEs, pull requests, CI/CD, and AI/ML pipelines, and overseeing continuous threat modeling and validation. Own security for AI systems, models, prompts, and agents, including adversarial testing for prompt injection, model abuse, and data leakage. Mentor engineers and promote automated, secure software development practices.

Lead application security engineering across the SDLC using AI-assisted threat modeling, automated security testing, vulnerability prioritization, and secure-by-default controls. Partner with Engineering, Product, QA, DevOps, and AI platform teams to secure applications, APIs, cloud infrastructure, data, and AI/ML systems. Build security automation, CI/CD controls, policy-as-code guardrails, developer enablement, and proactive defenses against emerging threats such as prompt injection and data poisoning.

Lead end-to-end Application Security product and program: set strategy, prioritize roadmap, ship AI-powered threat modeling and code-evaluation surfaces, enable secure-by-design SDLC, enforce CI/CD gates, drive vulnerability prioritization/remediation, establish governance and metrics, and align security initiatives with engineering and executive stakeholders.