Technical Leadership & Solution Ownership: Lead the technical direction of AI initiatives by driving architecture decisions, establishing best practices, mentoring team members, and guiding the end-to-end delivery of scalable AI solutions.
Kubernetes Service Platform Development of managed Kubernetes services with GPU-native orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, resource isolation, and support for large-scale AI training and inference workloads
Kubernetes Service Platform Development of managed Kubernetes services with GPU-native orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, resource isolation, and support for large-scale AI training and inference workloads
Based on Southeast Asia business scenarios and Agent applications, participate in designing AI business implementation scenarios to help improve business efficiency and solve business pain points.
Integrate AI Agents into daily R&D workflows and explore their applications in scenarios such as coding assistance, intelligent debugging, automated testing, issue troubleshooting, and business process automation.
Mentor junior AI engineers, set best practices for prompt engineering, RAG pipelines, and agent evaluation, and help build reusable AI infrastructure for the broader team.
Establish the runtime and governance framework for AI Agents, including execution isolation, permission control, auditability, evaluation, stability, and cost governance.