Drive the development of AI agent frameworks and automated engineering capabilities to support real product and project delivery.
Design and implement multi-agent collaboration workflows, tools, and engineering standards for scalable AI-assisted development.
Build and integrate AI-driven capabilities into existing microservices, backend systems, data platforms, and messaging infrastructure.
Enable AI agents to participate in feature development, automated testing, code generation, and validation with production-ready outputs.
Establish quality governance for AI-generated code, including code review practices, testing strategies, static analysis, performance optimization, and security checks.
Collaborate closely with product, backend, infrastructure, and cross-functional teams to define technical solutions, align priorities, and ensure smooth deployment.
Contribute to the evolution of AI-native software engineering practices and help shape the future of intelligent development workflows.
Requirements
3+ years of hands-on Java development experience in production environments (not coursework or side projects).
Strong experience in microservices and distributed systems, including multi-service architectures and multi-data-source integrations.
Solid understanding of backend technology stack including Redis, Kafka, and RDBMS (Oracle / MySQL / ClickHouse), with the ability to justify architecture and technology choices based on real business scenarios.
Strong SQL and database optimization skills, preferably with Oracle 11g/12c experience, including query tuning and performance troubleshooting.
Practical exposure to AI agent / LLM tooling such as Cursor, Claude Code, Cline, or similar AI coding agents.
Experience working with AI-assisted development workflows, multi-agent collaboration, or implementing guardrails and governance for AI-generated code is highly preferred.
Mandarin speaking capability is required to support collaboration with regional stakeholders and teams.