Sr./Staff AI Security Engineer

Job description

Join Trend ‧ Join New Generation 趨勢科技 - 全球雲端資安領航者 / 全亞洲最大軟體公司 / 企業版圖橫跨五大洲 / 趨勢全球研發基地在台灣 =============================================================== Trend Micro Incorporated, a global cloud security leader, creates a world safe for exchanging digital information with its Internet content security and threat management solutions for businesses and consumers. A pioneer in server security with over 30 years' experience, we deliver top-ranked client, server and cloud-based security that fits our customers' and partners' needs, stops new threats faster, and protects data in physical, virtualized and cloud environments. We are seeking a Senior/Staff AI Security Engineer to join Trend Micro's Global CISO Office GRC team. This role sits at the intersection of AI security and governance — responsible for assessing risks across our evolving AI landscape and embedding security practices throughout AI adoption. The ideal candidate builds security from real-world AI experience, not in isolation from it. We are looking for someone who understands how modern AI systems actually work — including agentic architectures, multi-agent systems, and AI data flows — and can translate that understanding into practical security controls and governance frameworks. Key ResponsibilitiesI. AI Security Risk AssessmentAI Threat Modeling & Risk Assessment: Lead the analysis and assessment of security and privacy risks across the evolving AI landscape, including large language models (LLMs), Generative AI services, agentic and multi-agent systems, and AI data governance Policy and Compliance: Collaborate with legal and compliance teams to ensure AI applications adhere to internal policies and external regulations (e.g., NIST AI RMF, EU AI Act, emerging AI-specific laws) Vulnerability Analysis: Study and document potential vulnerabilities within AI ecosystems and pipelines, including model integrity, training data exposure/leakage, inference endpoints, and agentic behavior risks Remediation Design: Design and recommend effective security controls and mitigations to address identified risks, translating security requirements into actionable engineering plans II. AI Security Implementation & EngineeringSecurity Service Implementation: Lead the technical implementation of specific AI-related security services, such as input/output content filters, adversarial defense mechanisms, and secure model serving architectures AI System & Data Security Implementation: Lead the design and implementation of security controls across AI systems — encompassing data governance, model integrity, access controls, usage policy enforcement, and compliance auditing — and embed security throughout the full AI Development Lifecycle (AI DLC), from data ingestion and model integration through to deployment and monitoring, championing a "security-by-design" approach across all AI initiatives Research & Advisory: Stay current with the rapidly evolving field of AI security and attack vectors. Provide expert consultation to product and engineering teams on best practices for secure AI development Required QualificationsBachelor's or Master's degree in Computer Science, Cybersecurity, or related field 5+ years of experience in software engineering, with at least 2 years hands-on experience building and deploying AI applications or AI platform engineering in production Proficiency in Python; experience with LLM APIs, prompt/context engineering, and AI agent or orchestration frameworks Practical experience with AI tooling: coding assistants (GitHub Copilot, Claude Code, Cursor, etc.), agentic runtimes, and CI/CD pipeline integration Familiarity with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes) Solid understanding of AI security risk concepts (e.g., prompt injection, data leakage, model misuse, agentic behavior risks) Strong communication skills — able to translate AI risk findings into clear, actionable language for both technical and non-technical stakeholders Preferred QualificationsExperience in AI/ML security, MLSecOps, or cloud-native security Familiarity with AI governance frameworks (NIST AI RMF, ISO 42001, EU AI Act) or security frameworks (NIST CSF, ISO 27001) Experience with shadow AI detection, NHI/agent identity management, or AI observability tooling Relevant certifications: CISSP, CISM, CRISC, or CAISP Familiarity with software supply chain security as it applies to AI models and training data =============================================================== 連結智慧 守護世界 --- Connected Intelligence for Securing a Connected World