Design and optimize the architecture of real-time risk control engines, lead the technology selection and development of core modules, ensuring the system supports millisecond-level response and high concurrency.
Build a multi-level risk control system to identify risky transactions, dynamically assess user risk levels, and implement mechanisms such as circuit breakers / rate limiting / auto-liquidation to meet the risk control needs of various business lines like spot, contracts, and options.
Lead major troubleshooting and performance optimization in production environments to ensure high system availability; build end-to-end monitoring systems for real-time alerting on core metrics and performance analysis.
Stay abreast of industry trends, promote the application of technological achievements, and continuously improve the design of the risk control system.
Requirements
Bachelor's degree or higher in Computer Science or a related field; 5+ years of backend development experience, including 3+ years developing financial risk control systems (securities, futures, cryptocurrency).
Proficient in at least one of Go / Java / Python / C++ / Scala; skilled in big data ecosystems and rule engines.
Experience in optimizing high-concurrency risk control systems; has led the design or optimization of core modules (e.g., real-time decision engine) and successfully resolved major production incidents.
Familiar with business scenarios such as high-leverage trading and derivatives; knowledgeable in risk measurement methods like VaR, stress testing, and scenario analysis, and capable of translating these into implementable technical solutions.
Proficient in performance bottleneck analysis, capable of improving risk identification accuracy through algorithm optimization; has practical chaos engineering experience, able to design stress testing plans to simulate extreme market conditions.
Nice-To-Have:
Experience developing core risk control systems at top-tier exchanges or financial institutions.
Experience developing risk management systems for hedge funds, asset management firms, or quantitative institutions.