Java Engineer - 4

創立於1993年美國矽谷，專注於寬頻接取與家庭網路解決方案，主要服務北美電信業者，累計出貨超過6,800萬台聯網設備，並獲得220多項產業獎項。

2024年12月，正式成立台灣子公司，聚焦於新一代網路設備的韌體開發與測試，持續拓展全球研發與工程能力。為 Cambridge Industries USA Inc. 全資子公司，隸屬於 CIG（Cambridge Industries Group），結合全球資源與技術實力，提供高效能、易於部署的網路產品與解決方案

• 5–8+ years of professional Java backend development with strong proficiency in Spring Boot, JPA, and MyBatis/Hibernate
• Solid hands-on experience building or operating Spark-based data processing workloads in production
• Practical experience with time-series databases (TDengine, InfluxDB, TimescaleDB, or equivalent)
• Proven experience integrating Kafka, MySQL, and MongoDB in production environments
• Strong understanding of high-frequency data processing, performance tuning, and concurrency control
• Proficiency with Git, Maven/Gradle, and CI/CD pipelines in team-based development
• Demonstrated ability to integrate AI tools into daily engineering workflows — including spec-driven practices such as defining architecture, constraints, and acceptance criteria before writing code — as consistent practice, not occasional experimentation
• Design, build, and optimize backend services using Java (Spring Boot) for high-throughput, data-intensive platforms
• Develop and operate batch and real-time data pipelines using Apache Spark
• Architect and manage time-series data solutions with TDengine or similar databases
• Integrate and orchestrate data flows across Kafka, MySQL, MongoDB, Hadoop, and S3-compatible storage
• Design high-performance, multithreaded processing models, scheduling mechanisms, and monitoring strategies
• Apply AI tools throughout design, code generation, refactoring, performance analysis, and incident investigation
• Practice Spec-Driven Development — define intent, architectural constraints, and acceptance criteria before implementation, using tools like GitHub Spec Kit to make specifications the single source of truth for AI agent code generation and validation
• Produce clear technical documentation including system diagrams, data flow designs, and architectural decision records
• Contribute to cross-language modules in Golang when applicable
• Collaborate with senior engineers to co-evolve platform architecture and data strategy