AI Native Platform Architect
OKX
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Interviews for architect roles keep coming back to AWS, Python, Azure, GCP. Practise those questions before you sit with OKX.
Questions you are likely to be asked
- Why do you want to join OKX?
- What is your experience with RAG? Tell me one thing you learned the hard way.
- Tell me about a time the data was messy or wrong. What did you do?
- How would you explain your model's result to someone who is not technical?
- What would you check first if a model's accuracy dropped after going live?
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Practise the AI Native Platform Architect at OKX interview free →Who We Are
About the Opportunity
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.
- 8+ 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!
Disclaimer: Please note that Hong Kong is a group-level service hub, and OKX does not carry on a business of operating a virtual asset trading platform in Hong Kong.
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Listed on greenhouse · posted 2026-04-15. ApplySarthi collects openings and links to application pages; the role is advertised by OKX, not by us.