Job Responsibilities
Design, develop, and maintain enterprise-grade backend systems using Java and Spring ecosystem, ensuring high performance, scalability, and reliability.
Lead the design and implementation of microservices architecture, including service decomposition, API design, and system integration.
Build and maintain RESTful / RPC APIs to support complex business scenarios and high-concurrency workloads.
Take ownership of core backend modules and frameworks, participating in system architecture design and technical decision-making.
Optimize system performance and stability, including JVM tuning, thread management, database optimization, and distributed system troubleshooting.
Build and maintain data pipelines and knowledge integration layers to support AI-driven business scenarios.
Collaborate with frontend, AI, data, and DevOps teams to deliver end-to-end solutions.
Follow best engineering practices, including code review, automated testing, CI/CD, and secure software development lifecycle.
Job Requirements
Proficiency in Java, with practical experience in development frameworks like Spring, SpringMVC, SpringBoot, MyBatis, JPA, and mainstream microservices frameworks (Spring Cloud, Dubbo), including an understanding of their core principles.
Solid foundation in data structures, algorithms, and object-oriented design, with strong engineering mindset and coding standards.
Proven experience with microservices architecture, distributed systems, and service governance (e.g., configuration, discovery, circuit breaking).
Hands-on experience with relational and NoSQL databases, including schema design, transaction management, and performance optimization.
Capable of writing and optimizing complex SQL statements and store procedures, able to build and maintain ETL, ensuring the efficiency and data consistency of the data storage layer.
Familiar with middleware and infrastructure components such as Redis, Kafka/RabbitMQ, Elasticsearch, and API gateways.
Experience with containerization and cloud-native technologies, including Docker and Kubernetes.
Proficient with development and DevOps tools such as Maven/Gradle, Git, and CI/CD pipelines.
A bachelor's degree or above in computer science, artificial intelligence, data science, software engineering, mathematics, or a related field is required; a master's or doctoral degree is preferred.
Ability to have good communicate in English, both written and verbal.
Experience in designing and delivering large-scale, distributed backend systems in production environments.
Hands-on experience in integrating AI or intelligent services into business systems is a strong plus, but not mandatory.
