About this role

▸about OKX — company background

Who We Are

At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom.

OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves.

Across our multiple offices globally, we are united by our core principles: We Before Me, Do the Right Thing, and Get Things Done. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er.

About the Opportunity

You will be responsible for the core architecture design and technical delivery of an enterprise-grade AI Native engineering platform, driving the deep integration of large language models, AI Agents, knowledge capabilities, and the software development lifecycle. The platform will support intelligent capabilities across requirement analysis, solution generation, coding collaboration, test automation, and environment orchestration.This role focuses on engineering-grade AI implementation in complex R&D scenarios. You are expected to turn model capabilities into reusable, scalable, and governable platform capabilities, and continuously drive the evolution of the engineering platform toward an AI Native architecture.

What You’ll Be Doing

• Lead the overall architecture design and core capability development of the AI Agent platform, including task orchestration, tool invocation, context management, memory mechanisms, and multi-agent collaboration.

• Drive the implementation of AI Native capabilities in engineering workflows, including AI coding, technical solution generation, test case generation, test report generation, and automated environment deployment.

• Build the knowledge augmentation layer for the platform, including the design, integration, and application of RAG, GraphRAG, and knowledge graph capabilities.

• Establish the runtime and governance framework for AI Agents, including execution isolation, permission control, auditability, evaluation, stability, and cost governance.

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