Product Manager Intern, Traffic & Content - LLM Feature (Fall 2026)

About the team Shopee will be prioritizing applicants who have a current right to work in Singapore, and do not require Shopee sponsorship of a visa. The minimum internship commitment period required is 3 months, and students who are available for 6 months would be preferred. Kindly note that you can only be considered in one recruitment process at a time within Sea Group and will be considered for jobs in the order that you have applied. We are seeking a highly motivated and execution-driven individual to develop LLM-powered capabilities that deepen our understanding of users and items within our marketplace. This role focuses on leveraging Large Language Models (LLMs) to generate high-quality user and item features that power downstream personalization, recommendation, search, ranking, ads, and other business functions. You will define how generative AI enhances marketplace intelligence and unlocks more relevant, contextualized shopping experiences. Responsibilities Identify high-impact use cases for generative AI across different business domains, translating advancements in LLM technology into practical product opportunities Develop clear product hypotheses grounded in user needs and business goals Write detailed product requirements (PRDs) for LLM features Collaborate with data scientists and developers on: Prompt design and orchestration, model evaluation & guardrails, balance tradeoffs between cost, latency, quality, and scalability Define evaluation frameworks (offline + online metrics) for LLM performance, measure and track success metrics for each feature Manage feature iteration cycles using experimentation and user feedback Requirements Relevant internship experience in E-commerce Strong understanding of Large Language Models, prompt engineering fundamentals, evaluation metrics for generative AI Ability to translate ambiguous AI capabilities into user-facing value Strong analytical skills and comfort with experimentation frameworks Technical (CS, engineering, data science) or equivalent degree Full-time interns preferred Part-time interns who can commit at least 3 working days a week are also welcome to apply