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AI Native Engineer (Vision One XDR Workbench)

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Onsite

AI Native Engineer (Vision One XDR Workbench)

TrendAI

AI Native Engineer (Vision One XDR Workbench)

Skills

DockerReactJavaAIAWSGitHubLinuxJavascript

2 months ago

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Important information


Contract type:

Permanent

Location:

Taipei, Taiwan

Work mode:

Onsite

Published on:

11 August 2026

What they need


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 The XDR capabilities of Trend Micro’s Vision One platform provide context-aware investigation, recording, and reporting of system-level activities across multiple security layers — AI App, endpoint, servers, cloud workloads, email, and networks. Workbench is a key component that helps security analysts cut through alert fatigue and respond to incidents quickly.

We’re evolving how the team builds software. This isn’t a role defined by a technology layer — it’s defined by how you think and work. AI is your primary tool for accelerating the full engineering cycle, and system thinking is how you use it responsibly. You’ll start with a domain you’re strong in and grow from there.

[Your Mission]

  • Start with one or two anchor domain — backend, frontend, or DevOps — and go deep. Over time, use AI as a bridge to build working knowledge across all three, not to replace specialists, but to collaborate without walls.
  • Invest in understanding the product domain and user workflows deeply enough to translate requirements into precise system specs — using BDD/TDD as the shared language between human intent and AI generation.
  • Integrate AI tools (e.g., GitHub Copilot, Claude Code) throughout the development lifecycle — from spec writing and test generation to code review and debugging — rather than using them as occasional shortcuts.
  • Own the full engineering cycle: from requirement to spec, AI-assisted implementation, architecture-aware review across frontend, backend, QA, and DevOps, through to data-driven validation that what we shipped actually solves the problem.
  • Use data as a feedback loop — monitor service signals (reliability) and track feature usage to validate outcomes, and feed those insights back into the next iteration.

Required

  • Bachelor’s degree or above in computer science or related fields.
  • Pick the domain you’re strongest in. This is where you’ll go deep first.
  • Backend — Experience in Java and AWS cloud services.
  • Frontend — Experience in browser JavaScript development, including React and core web technologies (HTML/CSS/JS).
  • DevOps — Experience in Docker/K8S/CI/CD and cloud infrastructure operations.
  • Hands-on experience with AI-native development tools (e.g., Cursor, GitHub Copilot, Claude Code) in a real project or side project.
  • Habit of critically reviewing AI-generated code rather than adopting it directly, with awareness of system-wide concerns such as API contracts, data models, and security boundaries.

Big Plus

  • Working knowledge beyond your anchor domain — frontend, backend, or DevOps.
  • Familiar with cloud infrastructure such as networking, security, and computing stack.
  • Experienced in operating products/services at large scale.

Deep understanding of networking and Linux operating systems.

  • Understanding of agent frameworks or common agent design patterns .
  • Familiarity with harness engineering techniques to guide AI toward higher-quality outputs.

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

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