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Trend Micro

AI Native Fullstack Engineer (Vision One XDR Workbench)

Reposted 2 Months Ago
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Remote
Hiring Remotely in Taipei
Mid level
Remote
Hiring Remotely in Taipei
Mid level
Build and own AI-assisted full engineering cycles for Trend Micro Vision One XDR workbench across frontend, backend or DevOps. Use AI tools to write specs, generate and review code, integrate across stacks, deploy on cloud, monitor service signals, and validate outcomes. Collaborate across domains using BDD/TDD and system thinking to deliver secure, scalable detection and investigation features.
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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. 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. 

 

[Your Entry Point] 

- 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. 

 

[Required — All Tracks] 

- Bachelor’s degree or above in computer science or related fields. 

- Hands-on experience with AI-native development tools (e.g., Cursor, GitHub Copilot, Claude Code) in a real project or side project. 

- Ability to write clear BDD/TDD specs that scope AI-assisted development — understanding that the quality of specs determines the quality of AI output. 

- Ability to provide effective context when working with AI — understanding that output quality depends on input quality. 

- 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

Trend Micro Toronto, Ontario, CAN Office

1 Snooker Street, Toronto, Canada, M6K 1G1

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