About The Role

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.

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.

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.