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Bybit, a leading cryptocurrency exchange and digital financial platform serving 80+ million users globally, is seeking a Senior Product Manager to lead end-to-end product development for AI and LLM-powered applications. This is a hybrid product builder role at an inflection point where AI is fundamentally reshaping product capabilities and user experiences.
You will own the full lifecycle of AI applications—from zero to one—across domains including intelligent customer service, personalized recommendations, AI assistants, and automated workflows. You are the critical connector between user insights, AI technical capabilities, and business objectives, capable of discussing RAG retrieval strategies and multi-agent orchestration with ML engineers while articulating product value and delivery roadmaps to business stakeholders.
Key Responsibilities:
- Own end-to-end AI product lifecycle management for intelligent chatbots, AI assistants, recommendation systems, and automated workflows, from requirements definition through launch and delivery. Produce high-quality PRDs, interaction flow diagrams, and acceptance criteria while driving cross-functional execution.
- Deeply engage in Agent product design, including task planning workflows, tool-calling strategies (Function Calling / MCP), context management, multi-agent orchestration logic, and graceful failure handling. Translate model capabilities into meaningful user value.
- Build AI evaluation frameworks—designing test scenario sets, evaluation metrics (accuracy, hallucination rate, task completion rate), and regression test libraries. Independently assess AI capability boundaries and drive continuous model iteration.
- Lead platform architecture planning for intelligent customer service and conversational assistant products, covering knowledge base design, dialogue flow, corpus annotation, intelligent reply generation, and case summarization. Optimize conversation quality and issue resolution rates using large-scale data analysis.
- Collaborate with ML and data teams to design recommendation strategies and personalization engines. Define generative UI product requirements and drive growth in CTR, conversion rate, and user retention. Establish attribution analysis frameworks.
- Identify opportunities to apply AI technologies (RAG, Prompt Engineering, multimodal capabilities) to concrete business use cases. Define product evolution roadmaps balancing technical feasibility, UX, and commercial value.
- Act as product owner in close collaboration with algorithm, engineering, data, design, operations, and business teams. Maintain strong ownership in a fast-moving AI-native environment and rapidly translate emerging AI capabilities into product innovation.
Requirements:
- 3+ years of product management experience, with at least 1 year of direct hands-on experience delivering AI application products, AIGC products, or Agent products. Must have fully shipped at least one AI-related feature module or standalone product.
- Deep understanding of mainstream AI technology productization: LLM Prompt Engineering, RAG architecture, Agent fundamentals (tool calling / task planning / context window management), and conversational system design. Ability to independently evaluate technical proposal feasibility.
- Proven ability to design AI product evaluation frameworks—independently defining metrics, building test case sets, and tracking performance through data analysis. Familiarity with A/B experiment design and strong data-driven decision-making mindset.
- Ability to write structured, logically rigorous PRDs, technical requirement documents, and flow diagrams. Excellent cross-functional communication skills bridging technical and business teams.
- Sharp ability to translate ambiguous user needs into clearly defined product requirements. Skilled at balancing AI capability boundaries with user expectations.
- Sustained enthusiasm for continuous learning in rapidly evolving AI landscape. Strong sense of ownership—able to proactively define problems, drive decisions, and take accountability in highly ambiguous environments.
Nice to Have:
- Familiarity with cutting-edge AI engineering practices: MCP (Model Context Protocol), Function Calling, multi-agent orchestration frameworks (LangChain / AutoGen / CrewAI).
- Experience with AI Harness / Eval / Benchmark platform product design or usage.
- Background in Fintech / e-commerce / SaaS with understanding of AI product design in high-concurrency, compliance-sensitive environments.
- Bilingual fluency in Chinese and English (spoken and written).
