• Define and own the enterprise security architecture for Generative AI systems, including LLM-based applications, agentic AI, and AI platforms • Partner with the AI Foundry to design secure GenAI platforms, tools, and workflows • Establish architectural standards and guardrails for AI system design, deployment, and operation • Embed secure-by-design principles into AI pipelines, including model access, data ingestion, inference, and output handling • Conduct architecture reviews to identify risks across AI systems, including data exposure, model misuse, and integration vulnerabilities • Publish Risk Assessment Reports that include threats and mitigating controls aligned to GEV policies and standards • Lead threat modeling and risk assessments for GenAI systems using frameworks such as: OWASP Top 10 for LLM Applications, OWASP Top 10 for Agentic Applications, MITRE ATT&CK / ATLAS (for AI threats) • Apply Zero Trust principles to AI systems, including identity and authentication for AI agents and services

• serve as a senior technical leader responsible for securing enterprise applications, data platforms, and digital services across cloud and hybrid environments • partner with application teams, data engineering, and platform teams to ensure that security is built into application design, development, and data lifecycle management from inception • lead the development of security strategies for enterprise applications, APIs, SaaS platforms (including M365), and data platforms such as Databricks • ensure alignment with enterprise policy, regulatory requirements, and Zero Trust principles • lead security architecture reviews for enterprise applications, APIs, and SaaS integrations to ensure alignment with security standards and policies • identify risks, control gaps, and non-compliant patterns across application and integration architectures • define required application security controls across the SDLC • provide architecture approvals, conditional approvals, and remediation guidance • publish Risk Assessment Reports that include threats and mitigating controls aligned to GEV policies and standards • define security architecture for data platforms (e.g., Databricks), data lakes, and analytics environments • establish controls for data classification, encryption, access governance, and secure data sharing • partner with data engineering teams to implement secure data pipelines and controls • lead threat modeling and risk analysis for applications, APIs, and data platforms using industry frameworks (e.g., MITRE ATT&CK, OWASP) • define and enforce secure design patterns for applications and integrations • ensure security controls are incorporated early in architecture and design phases • define secure integration patterns for M365, Microsoft Graph API, and SaaS platforms • review application permissions, identity models, and data access controls for SaaS integrations • ensure compliance with enterprise identity, access management, and governance standards

• Design and implement security measures to protect company data from unauthorized access, disclosure, and misuse. • Partner closely with the Detection & Response team to maintain full visibility into enterprise access, networks, and devices. • Deploy and manage security tools across Discord's corporate infrastructure. • Establish security standards that provide strong protection while enabling smooth workflows. • Develop and deliver security awareness training for employees. • Shape and enforce Discord's IT and security policies. • Build secure, sustainable environments using modern principles like "secure by design" and “zero-trust” network architecture, without relying on traditional VPN setups. • Foster a security-conscious culture by guiding employees on data protection best practices. • Partner cross-functionally with IT, Engineering, Workplace, and other teams to achieve security objectives

• Deliver major features and architectural improvements across the Add-ons stack, including automated moderation pipelines, Reviewer tools, and DevHub. • Create robust observability systems and data-backed insights. • Provide peer feedback, share knowledge and help others grow. • Improve platform reliability through deployments, monitoring, and incident response. • Help keep the platform safe and trustworthy, with attention to security and user trust. • Step in to resolve issues impacting users and developers, from small bugs to larger incidents. • Collaborate with designers, product managers, QA, and community contributors to deliver end-to-end improvements. • Contribute in the open through pull requests, code reviews, and discussions.