Trend Micro
AI Native Engineer (Vision One XDR Workbench)
Taipei
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- Seniority
- Mid level
- Country
- TW
- Work mode
- On-site / unstated
- First seen by hirly
- 27 Sept 2026
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the posting
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
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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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