Description
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Team Leadership — Build, manage, and develop a team of AI engineers and researchers; own hiring, growth, and performance across the function
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Agent Product Delivery — Lead end-to-end delivery of autonomous AI Agent products, covering the full lifecycle from requirements and architecture through to production operations
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Eval-Driven Development — Establish benchmark-driven evaluation frameworks that replace manual iteration with quantifiable quality signals across agent systems
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Agent Harness Design — Design and implement end-to-end Agent Harness infrastructure to ensure agent stability and reliability in complex, real-world scenarios
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LLM Orchestration — Orchestrate creative reasoning steps alongside deterministic guardrails, finding the right balance between flexibility and control
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Engineering Workflow Integration — Embed AI Agent capabilities deeply into core products and engineering pipelines, improving both developer productivity and business value
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Cross-functional Alignment — Collaborate with product, engineering, and business teams to ensure technical direction stays tightly aligned with strategic priorities
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Master's or PhD in Computer Science, Artificial Intelligence, or a related field (PhD preferred)
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10+ years of experience in AI/ML research, productization, or platform development, including core technical or leadership roles at globally recognized technology companies
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Deep expertise in LLMs and Generative AI, deep learning, reinforcement learning, recommendation systems, and related areas
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Proven track record of translating AI capabilities into measurable business outcomes
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End-to-end delivery experience with autonomous AI Agent products, from inception and architecture through to production operations
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Hands-on experience integrating AI deeply into engineering and development workflows — such as AI coding assistants, automated code review, or developer productivity tooling
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Proficiency in Mandarin and English is required to collaborate across our multilingual, cross-regional teams
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Background at an AI-native startup or frontier AI lab, with familiarity with fast-cycle product iteration
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AI publications, patents, or industry-recognized technical contributions
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Familiarity with the unique technical challenges of applying AI in crypto, fintech, or high-frequency data environments
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