Applied AI Engine Engineer in Test (Content Inspection, Shisa)

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Overview

We are looking for highly proactive, self-motivated and experienced engineers. This role is responsible for testing and evaluating the quality of Trend Micro Virus-Scan Engine and Advanced Threat Scan Engine which are used by many Trend Micro projects.

Below are some examples which you might be involved:

● Write/review codes to evaluate the quality (focus on C/C++/Perl/Python)

● Analyze and research emerging threats

● Collaborate with cross-functional teams to design threat detection patterns, review technical solutions, and deliver high-quality scan engines

● Create/Maintain automation scripts/process/system for testing

Qualification / Requirement

● BS or MS in Computer Science or related field

● Highly proactive, self-motivated and good team work

● Experience in programming languages (e.g. C, C++, Perl, Python)

● Experience in Windows Operating System

● Good English communication skills

AI Capabilities Requirement

In line with Trend Micro’s 2026 AI-first strategy, this role is expected to actively adopt AI tools into daily QA workflows and contribute to the team’s AI-driven testing transformation, including future AI DLC initiatives.

🎯 Your Mission

■ Leverage AI-native development tools (e.g., Claude Code, GitHub Copilot, Cursor) to design, automate, and optimize test workflows, improving testing coverage and efficiency across the content inspection pipeline.

🔍 What We’re Looking For

■ AI Tool Proficiency: Familiarity with AI-native development tools (e.g., Claude Code, GitHub Copilot, Cursor) and the ability to integrate them into daily QA activities such as test case generation, log analysis, defect triage, and code review.

■ AI-Assisted Test Workflow: Demonstrated experience building repeatable AI-assisted test workflows, including prompt engineering for test automation, context management, and leveraging agent-based tools (e.g., MCP servers, AI Agent Skills).

■ Content Inspection & AI DLC Testing: Experience applying AI tools to content-based testing scenarios, such as generating diverse malicious/benign sample sets, evaluating

detection accuracy, or assisting in validating AI-driven detection logic and classification models.

⭐ Extra Skills We Love

■ Team AI Enablement: Experience driving team-level QA improvements by standardizing AI-assisted workflows, including documentation, knowledge sharing, and onboarding teammates to new AI tooling.

■ AI Detection Model Testing: Exposure to AI-powered detection or classification models, and experience designing test strategies to validate their output quality, edge cases, and regression behavior.

🌱 Culture Fit

■ Passionate about applying AI to solve real-world QA challenges; proactive in exploring new tools and sharing learnings with the team.

■ Embraces experimentation and continuous learning in a fast-evolving AI landscape.

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