AI流程改造专家-供给侧流程

优缺点分析

角色解读

• Progress to senior AI transformation lead or head of operational excellence within the region.
• Deepen expertise in AI-native process design and become a thought leader in applying LLMs to real-world business.
• Transition to broader strategy roles overseeing digital transformation across multiple markets.
• Identify and redesign key supply-side processes (e.g., merchant onboarding, campaign management) using AI to boost efficiency and reduce costs.
• Collaborate with product, engineering, and operations teams to define AI feasibility, design fallback mechanisms, and oversee rollout.
• Establish metrics and monitoring frameworks to measure before/after improvements and iterate continuously.
• Keep abreast of latest AI/LLM advancements and evaluate new opportunities for process optimization.
• Deep understanding of LLM capabilities and limitations (hallucination, latency, cost) and practical experience with human-in-the-loop designs.
• Strong process decomposition and abstraction skills to convert ambiguous business problems into structured workflows.
• Data-driven mindset to define problems, validate results, and build indicator systems.
• Excellent cross-team collaboration to align product, R&D, and operations with a shared vision.

申请策略

• Research Didi's Food business and its specific operational challenges to tailor your examples.
• Prepare to discuss a past project in detail: the problem, AI solution, team coordination, and results.
• Emphasize end-to-end ownership of an AI-driven process transformation, including specific metrics and outcomes.
• Showcase ability to translate business needs into technical requirements and collaborate with engineering teams.
• Highlight any experience with merchant-side operations or supply-side processes.
• Include examples of data analysis and dashboard creation for monitoring KPIs.
• Deepen hands-on experience with LLM APIs and prompt engineering if not already proficient.
• Learn about AI agent frameworks and orchestration tools (e.g., LangChain, AutoGPT).

面试指南

• Use the STAR method (Situation, Task, Action, Result) to structure examples.
• Emphasize data-backed decision-making and iterative improvement.
• Show balance between technical understanding and business impact.
• Describe a time you led an AI-driven process change. What were the key challenges and how did you overcome them?
• How do you decide when to use AI vs. rule-based automation in a process?
• What metrics would you track for a merchant onboarding flow after introducing AI?
• How do you handle situations where the AI model's accuracy is insufficient?
• How would you convince a skeptical product manager to adopt an AI solution?