Risk Control System Development Engineer

RedotPay is a global cryptocurrency payment fintech company dedicated to integrating blockchain solutions into traditional banking and financial infrastructure. Our user-friendly crypto platform empowers millions worldwide to use and transfer digital assets, delivering faster, more convenient, and more inclusive financial services. RedotPay promotes financial inclusion for the unbanked, supports cryptocurrency enthusiasts, and drives global adoption of secure and flexible crypto‑financial solutions. Join us to shape the future of finance and make a profound impact worldwide. Responsibilities Build a dedicated risk‑control data warehouse and design real‑time/offline feature processing pipelines, achieving a closed‑loop from data collection, cleaning, and storage to feature services. Integrate machine learning models (e.g., anti‑fraud, credit scoring) with rule‑based strategies, and develop automated model deployment and A/B testing frameworks. System Implementation & Performance Optimization Lead coding of core modules in the risk‑control system, resolving performance bottlenecks under high‑concurrency traffic to ensure 99.99% system availability. Establish monitoring and alert systems, design disaster recovery solutions, and ensure both effective risk interception and system stability. Drive seamless integration of risk‑control systems with business systems (payments, transactions, user center). Define API interface specifications and data integration standards. Documentation & Knowledge Sharing Write technical documentation, consolidate methodologies for system development, and cultivate team expertise in risk‑control technologies. Qualifications Core Technical Skills Programming Languages & Frameworks Proficient in Java; familiar with microservice frameworks (Spring Cloud/Dubbo/Gin). Skilled in cloud‑native technology stacks (Docker/Kubernetes/Service Mesh), with experience in containerized deployment and operations. Experienced with Flink/Spark Streaming for real‑time feature computation engines. Familiar with Kafka/Pulsar message queues. Knowledge of large‑scale data storage technologies: relational databases (MySQL/PostgreSQL), NoSQL (HBase/Redis/ES), OLAP (ClickHouse/Doris). Risk‑Control Specific Technologies Familiar with rule engines (Drools/Aviator) and decision flow engines (Camunda/custom). Skilled in the full cycle of risk feature engineering: feature extraction, real‑time feature services (Redis/Flink State), feature monitoring. Knowledge of model engineering tools: TensorFlow Serving/MLflow, and A/B testing frameworks. Data & Algorithm Capabilities Experienced in implementing common risk‑control algorithms (GBDT, XGBoost, Graph Neural Networks), integrating models with rule strategies. Skilled in SQL query optimization, designing efficient real‑time/offline data pipelines. Basic data analysis skills: able to validate feature effectiveness and interpret risk reports using Python/Pandas. Engineering Capabilities Familiar with full DevOps lifecycle: requirements to deployment, code management (Git/GitLab), CI/CD (Jenkins/Argo CD), monitoring (Prometheus/Grafana). Expertise in high‑availability system design: disaster recovery (multi‑active architecture/data backup), rate limiting & circuit breaking (Sentinel/Hystrix), performance tuning (JVM/thread pool/GC). Industry Knowledge Familiar with financial‑grade risk‑control standards: payment risk control (PCI DSS), anti‑money laundering (AML), data privacy (GDPR). Knowledge of black‑hat attack methods (credential stuffing, cash‑out fraud, bonus abuse), with ability to design targeted defense strategies. Mandatory Requirements Must have led technical selection for risk‑control systems (e.g., self‑developed rule engine vs. open‑source adaptation vs. commercial product procurement). Must have architecture design experience for complex scenarios (e.g., hybrid architecture supporting both real‑time anti‑fraud and offline credit evaluation). Seniority level Not Applicable Employment type Full‑time Job function Information Technology #J-18808-Ljbffr