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(Sr.) Software Engineer - Email Security

External
Trend Micro logoTrend Micro · Taipei, Taiwan
Full-timeOn-siteToday
ApacheAWSDockerGitHubKubernetesLinux
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Requirements

  • Python and/or PHP experience.
  • Apache server and RESTful API familiarity.
  • Email protocol knowledge: SMTP, POP3, IMAP, MTA.
  • Containerization experience (Docker, Kubernetes, AWS ECS).
  • Cloud services experience (e.g., AWS).
  • Personal AI workflow setup (CLAUDE.md, .cursorrules, prompt libraries, etc.).
  • ===============================================================
  • 連結智慧 守護世界 --- Connected Intelligence for Securing a Connected World

Additional Information

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 =============================================================== [Overview] We build enterprise email security products - spanning on-premises and cloud - covering core inspection engines, threat detection pipelines, and platform integrations that protect organizations worldwide. Our team focuses on core technologies - including Trend Micro's email inspection engine and defense solution platform - delivering high-quality security features with a strong engineering culture, where AI-native tools are a natural part of how we plan, build, and ship. We are looking for engineers who treat AI as a core part of their craft - using it to move faster, think deeper, and raise the bar on output quality. [Your Mission] Design and develop email security features across on-premises and cloud environments. Leverage AI-native tools (e.g., Claude Code, Codex, Cursor, GitHub Copilot) throughout the full development lifecycle - planning, design, implementation, testing, deployment, and operations. Critically evaluate and verify AI-generated output, maintaining the same engineering rigor as handwritten code. Collaborate with PMs, QA, and cross-functional stakeholders on requirements, design, and troubleshooting. [Qualifications] Essential BS in Computer Science or equivalent. Familiarity with Linux system programming. Hands-on experience with AI-native dev tools (Claude Code, Codex, Cursor, GitHub Copilot, etc.). Ability to provide effective context to guide AI toward production-quality outputs.


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