AI scenarios: Participate in the application of AI in front-end development and core business scenarios, helping build an AI-driven R&D and system capability framework. This includes, but is not limited to, improving development efficiency through AI, such as code generation, workflow-driven development, and business understanding; participating in the design and practice of AI Native / Agentic Commerce capabilities, including interaction models and capability abstractions for agents; exploring and contributing to cutting-edge AI payment capabilities and industry-standard protocols; and promoting intelligent capabilities across payment and financial flows, such as decision intelligence, recommendation intelligence, and experience intelligence, to continuously improve engineering efficiency and business outcomes.
AI scenarios: Participate in the application of AI in client-side development and core business scenarios, helping build an AI-driven R&D and system capability framework. This includes, but is not limited to, improving development efficiency through AI, such as code generation, workflow-driven development, and business understanding; participating in the design and practice of AI Native / Agentic Commerce capabilities, including interaction models and capability abstractions for agents; exploring and contributing to cutting-edge AI payment capabilities and industry-standard protocols; and promoting intelligent capabilities across payment and financial flows, such as decision intelligence, recommendation intelligence, and experience intelligence, to continuously improve engineering efficiency and business outcomes.
Contribute to the project's foundational knowledge by documenting the shared technical understanding and implementation details aligned with high-level business requirements and project goals.
Thrive in a fast-paced environment, engaging in technical operations and on-call rotations to address incidents related to cloud, OS, network, performance, and reliability.
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.
Explore and develop a risk-control Agentic AI architecture, including the design and optimization of Skills, long-chain task orchestration, and multi-agent collaborative problem-solving, to improve the efficiency of risk identification and incident resolution.
Problem Solving for Governance Applications: Address challenges such as long text/sequence modeling, few-shot learning, content moderation, violation detection, and policy recommendation using large models and multimodal approaches.