Role overview
Job Requirements:
• Over 3 years of experience in automated testing, with participation in at least 1 complete financial/trading system testing project, and familiarity with matching engines, API interfaces, risk control systems, and related business domains. • Proficient in at least one mainstream programming language (Python, Java, Go), with the ability to develop automated testing frameworks (e.g., Selenium, TestNG, Pytest, etc.). • Hands-on experience in API testing (Postman, RestAssured), performance testing (JMeter, Locust), and UI automation testing (Selenium/Appium). • Familiarity with AI testing technologies and practical experience applying AI in software testing, such as: • Reinforcement Learning (RL) to simulate real trading behaviors • AI-driven intelligent data generation to improve test coverage • AI anomaly detection to monitor trading patterns and API responses • Knowledge of cryptocurrency exchange-related business, including matching mechanisms, KYC/AML risk control, and market monitoring; priority given to candidates with experience in blockchain or financial system testing. • Familiarity with CI/CD processes and the ability to integrate automated testing into environments like Jenkins or GitLab CI.
Job Responsibilities:
- Trading Matching and Core Business Testing
• Design and execute automated regression tests to ensure the stability of core functions such as trade matching, order placement, and order cancellation. • Build high-concurrency trading simulation tests to validate the performance and accuracy of the matching engine under extreme market conditions. • Use Reinforcement Learning (RL) to simulate real trading behaviors and optimize test coverage for trade matching.
- API Automation Testing
• Utilize automated testing tools (Postman, RestAssured, JMeter, etc.) to test REST/WebSocket API interfaces, ensuring the stability of trading interfaces. • Leverage AI-driven intelligent test data generation to automatically create high-quality API test cases and improve coverage. • Apply anomaly detection algorithms to analyze API response times and traffic patterns, identifying potential issues.
- AI-Driven Risk Control and Security Testing
• Design automated risk control tests to validate the stability of KYC, AML (anti-money laundering), and trading risk control systems. • Use machine learning to analyze trading behaviors and identify abnormal transactions (e.g., spoofing, wash trading). • Employ AI pattern recognition technology to automatically detect market manipulation behaviors and enhance security.
- Frontend Automation Testing (Web + App)
• Use Selenium/Appium to conduct UI testing for the exchange’s frontend, ensuring compatibility across different devices and browsers. • Integrate AI visual regression testing to automatically detect issues with page layouts, K-line charts, market data misalignment, etc.
- High-Concurrency Stress Testing
• 使用JMeter、Locust等工具模擬大量交易，測試交易所的TPS（每秒交易量）、匹配延遲、同時處理能力。 • 結合人工智慧驅動的瓶頸分析來預測系統負載能力並優化交易所的架構。
獎勵積分：
• 具備AI+自動化測試專案經驗，專注於智慧測試優化。 • 了解智慧合約安全測試，熟悉區塊鏈攻擊方法（例如，重入攻擊、溢位攻擊）。 • 具有高並發交易系統優化經驗，具有分析和解決撮合引擎性能瓶頸的能力。