Responsibilities
- Lead the recruitment, development, and performance management of a team of AI researchers and engineers
- Oversee the full lifecycle delivery of autonomous AI agent products, from concept and system design to live operations
- Implement evaluation frameworks driven by benchmarks to automate quality assessment across AI agent systems
- Develop comprehensive Agent Harness infrastructure to maintain stability and reliability under real-world conditions
- Balance creative AI reasoning with controlled, rule-based safeguards in large language model orchestration
- Integrate AI agent capabilities into core engineering workflows and product development pipelines
- Align technical strategy with business objectives through collaboration across product, engineering, and business units
Requirements
- Advanced degree in Computer Science, Artificial Intelligence, or a closely related discipline
- Minimum of 10 years of professional experience in AI/ML research, product development, or platform engineering at leading technology organizations
- Extensive knowledge of large language models, generative AI, deep learning, reinforcement learning, and recommendation systems
- Demonstrated success in converting AI capabilities into tangible business results
- Proven experience delivering autonomous AI agent systems from initial design through to production deployment
- Direct experience embedding AI tools into software development workflows, including coding assistants or automated code review systems
- Fluency in both Mandarin and English to support collaboration across international teams
Nice to Have
- Experience at an AI-first startup or cutting-edge AI research lab with exposure to rapid product iteration
- Published research, patents, or recognized technical contributions in the AI field
- Understanding of AI challenges in cryptocurrency, financial technology, or high-velocity data environments
Preferred
- Background at an AI-native startup or frontier AI lab, with familiarity with fast-cycle product iteration
- AI publications, patents, or industry-recognized technical contributions
- Familiarity with the unique technical challenges of applying AI in crypto, fintech, or high-frequency data environments
