M
Metaverse Cloud Solution Limited
Java Development Manager
Skills
DockerJavaSpring BootRKafkaRedisAIKubernetesFullstack Development
2 months ago
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Important information
Contract type:
Permanent
Work mode:
Onsite
Published on:
10 August 2026
What they need
Responsibilities:
- Lead and coordinate the development team in agile iterations to achieve project development goals; manage code quality and timeline risks to ensure high-quality and on-time project delivery.
- Design the technical architecture and develop the core modules for Java projects.
- Spearhead system performance optimization and tackle critical, complex technical challenges.
- Participate in requirement analysis and technical proposal reviews, driving continuous system evolution.
- Empower Java developers and elevate overall team technical capabilities through code reviews, technical sharing, and hands-on mentoring.
- Maintain existing systems with the ability to rapidly locate and resolve online/production issues.
Requirements:
- 5+ years of Java development experience; strong communication, coordination, and teamwork skills, with the ability to assume technical management responsibilities and drive efficient team operations.
- Expert in socket communication, proficient in NIO programming, Netty, etc.
- Familiar with K8s; clear understanding of Kubernetes core concepts and architecture, mastery of high-availability design principles, and proficiency in Docker containers alongside an understanding of the relationship between K8s and Docker.
- Highly proficient in Java programming with a solid foundation; deep understanding of Java runtime principles, JVM, web development, distributed transaction processing, distributed files/caching, and message middleware.
- Hands-on experience with mainstream open-source frameworks: Spring MVC, Spring, Spring Boot, Dubbo, Kafka, Zookeeper, MyBatis, Redis, etc. Deep insight into open-source framework source code is highly preferred.
- Prior development experience in financial trading, copy trading, or MT5 (MetaTrader 5) is highly preferred.
- Proven ability to leverage AI tools to enhance efficiency and delivery quality; practical experience integrating AI tools into R&D workflows (e.g., standardizing development pipelines, CI/CD, and API testing into AI assistants, Skills, MCPs, or Runbooks) is highly preferred.
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