Sr./Staff AI Security Engineer

Location: Taipei

Time Type: Full time

Job Description

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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 
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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 Responsibilities

I. AI Security Risk Assessment

• AI 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 & Engineering

• Security 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 Qualifications

• Bachelor'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 Qualifications

• Experience 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

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連結智慧 守護世界 --- Connected Intelligence for Securing a Connected World