Senior/Staff Engineer, AI Agent Development

OKX will be prioritising applicants who have a current right to work in Singapore, and do not require OKX's sponsorship of a visa. 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. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. 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. - Collaborate with product, engineering, QA, and operations teams to standardize, productionize, and scale platform capabilities, continuously improving engineering efficiency and delivery quality. What We Look For In You - Bachelor’s degree or above, preferably in Computer Science, Software Engineering, Artificial Intelligence, or related fields. - 6+ years of experience in backend engineering, platform engineering, or infrastructure engineering, with strong system design and delivery capabilities. - Proficient in Java / Python, with solid coding skills, architectural thinking, and experience building complex systems. - Strong understanding of LLM and AI Agent architectures, including task decomposition, tool use, context management, memory, execution loops, and exception handling. - Hands-on experience with LangChain and LangGraph, and strong familiarity with mainstream AI coding tools or frameworks such as Claude Code, Codex, Cursor, and Copilot. - Experience in designing or developing RAG / GraphRAG / knowledge graph solutions for enterprise knowledge augmentation and engineering use cases. - Good understanding of DevOps, CI/CD, Kubernetes, and cloud-native technologies, with strong cross-functional collaboration and execution skills. Nice to Haves - Experience contributing to open-source projects related to AI Agents, AI Coding, RAG, or knowledge graphs. - Experience building enterprise engineering platforms, DevOps platforms, or AI platforms. - Familiarity with open-source Agent projects such as openclaw, openhands/openharness, or Hermes. Perks & Benefits - Competitive total compensation package - L&D programs and Education subsidy for employees' growth and development - Various team building programs and company events - Wellness and meal allowances - Comprehensive healthcare schemes for employees and dependants - More that we love to tell you along the process! Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX's Candidate Privacy Notice.

Bachelor’s degree or above, preferably in Computer Science, Software Engineering, Artificial Intelligence, or related fields. 6+ years of experience in backend engineering, platform engineering, or infrastructure engineering, with strong system design and delivery capabilities. Proficient in Java / Python, with solid coding skills, architectural thinking, and experience building complex systems. Strong understanding of LLM and AI Agent architectures, including task decomposition, tool use, context management, memory, execution loops, and exception handling. Hands-on experience with LangChain and LangGraph, and strong familiarity with mainstream AI coding tools or frameworks such as Claude Code, Codex, Cursor, and Copilot. Experience in designing or developing RAG / GraphRAG / knowledge graph solutions for enterprise knowledge augmentation and engineering use cases. Good understanding of DevOps, CI/CD, Kubernetes, and cloud-native technologies, with strong cross-functional collaboration and execution skills.

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. Collaborate with product, engineering, QA, and operations teams to standardize, productionize, and scale platform capabilities, continuously improving engineering efficiency and delivery quality.