Build the next generation of intelligent products that combine data, AI, and growth.
Product engineer with deep expertise in AI-driven product growth and large-scale system design. Experienced in building end-to-end pipelines from web/mobile frontend to backend, data infrastructure, and experimentation frameworks.
New User Acquisition – Own the full free-trial signup and conversion pipeline (UI, backend services, sales/self-serve integration).
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AI-enhanced Feature Adoption – Lead the design and implementation of Winterfest, an internal promotion platform delivering personalized feature recommendations powered by predictive models. Integrated targeting algorithms that adapt in real time to user behavior, increasing promotion-driven feature usage by 50–100%.
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Established AI-assisted engineering workflows, standardizing LLM-based coding, automated test generation, and documentation creation.
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Built an internal AI-driven dashboard tool leveraging RAG on high-quality past queries to accelerate data analysis and query generation for North Star metric tracking.
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Partner with PMs, data scientists, and engineers to define North Star metrics, run controlled experiments, and scale successful strategies.
Built a chat-based creation interface in Effect House, allowing creators to design custom video effects with natural language prompts powered by GPT-based language models.
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Designed scalable backend APIs for effect rendering and processing in TikTok’s effect backend.
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Contributed to model evaluation and prompt engineering strategies to balance creativity, safety, and performance in production deployment.
