Lead a project team to deliver end-to-end projects across the software development life cycle
Realizing business goals through implementing features to Shopee as a platform, including but not limited to return and refund, and clearing and settlement.
Use AI coding tools throughout the development lifecycle, including design, coding, testing, debugging, refactoring, and code review.
Build AI-native engineering practices, including Agent Harnesses, engineering Knowledge Bases, AI Loops, workflow automation, and knowledge reuse.
Collaborate in a highly cross-functional environment with Software Engineers, Product Managers, Quality Assurance Engineers, and Operation Engineers to deliver impact.
Guide and review technical designs and coding outputs of the team, taking responsibility for progress and quality of projects
Optimize the process of developing, debugging, testing, releasing, documenting, monitoring and operating on the cross-stack systems in the team
Design well layered engineering architectures to model product requirements, abstract reusable components, and decouple independent modules
Set the technical direction of the backend architecture, plan deliverables and milestones to execute the team's engineering strategy
Mentor and coach team members on backend software engineering principles and practices
Cultivate technical culture and innovation, and enhance engineering quality on a cross-team level
Requirements:
Bachelor's or a higher degree in Computer Science or related qualifications
At least 6 years of experience designing and troubleshooting highly scalable and maintainable distributed systems
At least 2 years of hands-on technical leadership experience, defining technical direction and leading project teams
Hands-on proficiency in an object-oriented programming language, such as Golang, Python, Java, or C++.
Hands-on experience in backend engineering middleware internals, such as MySQL binary logs, Kafka replication details, and Redis high availability strategies.
Experience in refactoring systems based on complex product requirements, to improve maintainability and development efficiency
Prior experience using AI to improve testing, debugging, incident response, code quality, or production operations in an implementation setting will be a strong plus.
