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Enterprise AI cybersecurity platform with layered protection, cyber risk exposure management and SecOps—62 global offices, the United Kingdom office is in London.

Responsibilities

  • Oversee technical support quality for the consumer market across client-side and backend systems (Cloud backend, AI Agent Q&A workflows, and billing/payment gateways); perform QA debugging to rapidly pinpoint root causes, gather comprehensive logs, and reproduce issues.
  • Lead the implementation of E2E test automation by converting uncovered customer-reported issues into automated test cases and corresponding user documentation, systematically boosting product quality and reducing recurring support tickets.
  • Monitor post-launch consumer reviews and complaints; leverage AI/Chatbot and Google Analytics (GA) data to proactively improve self-service coverage, transforming complex technical processes into systematic SOPs and customer-facing guides.
  • Design semi-automated verification mechanisms and standardized validation SOPs for non-automatable manual billing, payment, and licensing workflows to mitigate operational risk.

Qualifications

  • Deep understanding of software QA methodologies, tools, and processes, with the ability to independently analyze client-side (App/UI) and backend (billing, licensing) issues, collect complete logs, and reproduce defects.
  • Proficiency in Python or Shell Script to independently author and maintain high-quality automation test scripts.
  • Extensive experience with test automation frameworks and at least one mainstream UI automation tool (Playwright, Appium, Selenium), capable of designing and executing full E2E tests spanning UI and backend layers.
  • Hands-on experience integrating tests into CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI).
  • Familiarity with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
  • Strong communication skills in both Chinese and English.
  • AI-Assisted Development Skills:
    • Practical experience applying AI-native development tools (e.g., Cursor, GitHub Copilot, Claude Code) in production or personal projects.
    • Ability to provide effective context to AI (understanding that output quality heavily depends on input quality).
    • Habit of critically reviewing AI-generated code rather than accepting it blindly, alongside optimizing for token efficiency.

Nice to Have

  • Ability to interpret GA and Chatbot metrics to proactively identify customer issue distributions and trends, translating insights into actionable workflow improvements.
  • Experience in mobile testing (iOS/Android).
  • Hands-on experience with performance testing tools (e.g., JMeter, Locust).
  • Experience working in Agile/Scrum development environments.
  • Positive mindset, high maturity, and strong collaborative skills.
  • Strong logical reasoning and problem-solving abilities.

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Work setup

Location
Taipei
Remote work
In office
Employment
Full-Time