Job Description
- Develop backend services for real-time fraud detection, transaction monitoring, and risk analysis.
- Build and maintain scalable microservices to support risk assessment models and rule-based detection systems.
- Integrate machine learning models and risk scoring engines into backend systems.
- Participate in AI-assisted development initiatives, including automated code generation, intelligent alerting, and integration of LLM-powered risk operations tools.
- Proficiency in Java (Spring Boot), basic frameworks, such as multithreading and networking.
- Understanding of distributed systems, and Spring microservices, dubbo.
- Experience with SQL & NoSQL databases (MySQL, Redis, Hive, Starrocks).
- Familiarity with message queues & streaming (Kafka, RabbitMQ).
- Enthusiasm for and hands-on experience with AI-assisted development tools (e.g., Claude Code, GitHub Copilot, Cursor, or similar coding assistants); ability to leverage AI to accelerate code generation, code review, and unit test coverage.
- Basic understanding of how LLM/Agent systems work and how they integrate into backend services; interest in building or iterating AI-powered risk automation features.
- Familiarity with prompt engineering concepts and the ability to work alongside AI models in daily development workflows.
- Strong analytical thinking, excellent teamwork skills, and a keen ability to learn and adapt quickly.
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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