Job Responsibilities:

1. Own end-to-end planning and delivery for agent product initiatives, including user insights, scenario breakdown, PRD creation, roadmap management, release acceptance, post-launch review, and continuous iteration.

2. Identify high-value agent use cases across office and home scenarios; design the product path from demo and PoC to scalable delivery, with clear success metrics and business value.

3. Define core agent capabilities and experience boundaries, including task decomposition, multi-turn interaction, memory, context management, tool use, permission confirmation, fallback handling, and observability.

4. Collaborate with algorithm, engineering, design, and hardware teams to productize model capabilities, on-device inference, memory/knowledge bases, plugins/connectors, and workflow capabilities.

5. Develop product narratives, demos, solution materials, and launch playbooks for customers, sales teams, and partners; support key-customer co-creation, GTM, and ecosystem collaboration.

6. Continuously track trends in agents, LLMs, on-device models, automated workflows, and the AI hardware ecosystem; translate market and competitive insights into product strategy.

Job Requirements:

1. 3+ years of experience as an AI software product manager; experience with AI hardware or on-device models is preferred.

2. Understand the fundamentals of LLM applications and be familiar with key concepts such as agent workflows, memory, and agent evaluation.

3. Understand on-device and hardware product constraints, with attention to computing power, latency, connectivity, privacy, wake-up experience, voice/vision interaction, and device control.

4. Ability to write clear PRDs, solution documents, product stories, and customer-facing materials; willing to explore the new ways of software define, such as build the demo directly

5. Strong cross-functional cooperation skills, with the ability to build alignment among algorithm, engineering, design, hardware, business, and customer teams, and drive complex projects to delivery.

6. Strong English communication skills and the ability to use English as a working language.

7. Passionate about AI-native products, willing to learn new technologies quickly, and able to make pragmatic product judgments with attention to reliability, usability, cost, and real business value.

8. Highly proactive, innovative, and ownership-driven; able to identify problems, form hypotheses, validate quickly, and drive outcomes.

9. Hands-on experience with agent products, with the ability to use tools such as Claude Code, Codex, OpenClaw, and Genspark to build prototypes, validate workflows, and improve personal productivity.