Software Engineer (Backend, Java) - Risk

AsiaRemoteFull-time: Remotemid

EngineeringBackend Developer

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Quick Summary

Overview

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users.

Technical Tools

anthropicjavakafkamysqlredisspring-bootsqlcode-reviewdistributed-systemsmachine-learningmicroservicesnetworking

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.

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.