• Design and implement automated systems to monitor, detect, and mitigate security risks across infrastructure, application, and AI layers. • Lead efforts to integrate continuous security testing into CI/CD pipelines (SAST, DAST, dependency scanning, container scanning, etc.). • Build and maintain automated alerting and remediation workflows for security events. • Architect and implement robust authentication and authorization frameworks for end users, ensuring secure, scalable access control across web, mobile, and API surfaces (e.g., OAuth 2.0, SSO, role-based and attribute-based access models). • Harden cloud environments (AWS, GCP) and enforce least-privilege IAM, network segmentation, and encryption standards. • Conduct architecture reviews, threat modeling, and code audits to ensure secure design across all services. • Collaborate with engineering teams to define secure coding standards and best practices. • Develop security frameworks and tooling to detect and prevent LLM-specific vulnerabilities (e.g., prompt injection, data leakage, malicious model responses). • Implement guardrails for AI systems, including content filtering, input validation, and output sanitization. • Partner with our AI engineering team to design safe orchestration between models, APIs, and user data. • Own and continuously improve our incident detection, response, and recovery processes. • Collaborate on internal audits and compliance efforts. • Serve as a key advisor on emerging threats, vulnerabilities, and evolving best practices.