Partner with Tech Owners, frontend engineers, and Skill design leads to learn how business requirements are broken down into shippable, testable, production-ready product specs. Web3 Use Case Research
Research and map high-value, deployable Agent use cases across Web3 Wallet, Account, Payment, Trading, and other Binance business lines. Industry Tracking
Stay current on AI Agent, MCP, tool-calling, prompt engineering, and automated evaluation developments — and translate insights into product ideas for the team. Metrics & Quality
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Web3 Use Case Discovery: Map high-value, deployable Agent use cases across Web3 Wallet, Account, Payment, Trading, and other Binance business lines.
Industry Tracking: Stay current on AI Agent, MCP, tool-calling, prompt engineering, and automated evaluation developments — and translate them into executable product initiatives for the team.
Metrics & Quality: Define and track Agent performance metrics, including task success rate, user satisfaction, error rate, response quality, and tool-calling accuracy.
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Explore and integrate AI capabilities into mobile applications, including on-device AI inference, LLMs, intelligent agents, and AI-powered user experiences.
Design and optimize AI-related components for mobile and edge devices, with a focus on inference latency, memory usage, CPU/GPU utilization, power efficiency, and overall user experience.
Collaborate with cross-functional teams to define, design, and deliver new features across Android, iOS, and shared C++ infrastructure.
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Real-world Feedback Loops: Leverage multi-channel user feedback and real-world task data as primary research signals; design experiments and datasets to continuously improve agent and retrieval performance in production scenarios
2-8+ Year hands-on experience with LLM, RAG and AI agent systems in production
RAG & Agentic RAG Engineering: Hands-on experience building production retrieval pipelines end-to-end — embedding models (BGE, OpenAI, etc.), vector stores (Qdrant, Milvus, Pinecone, Weaviate), hybrid search (keyword + vector), reranking models; deep understanding of chunking strategy, text cleaning, and multimodal data parsing; experience implementing Agentic - RAG patterns — Self-RAG, Corrective RAG, adaptive retrieval, multi-hop decomposition, retrieve-reflect-refine loops
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