AI Architecture AI架构师

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What you'll do Continuously develop and upgrade the Architecture Team’s core services (API gateways, service registration and discovery, load balancing, etc.) to ensure system stability and scalability Provide highly available, high-concurrency, low-latency technical solutions for various company initiatives and business scenarios to support rapid business iteration Continuously build company-wide technical infrastructure, including shared development tools, code toolkits, and middleware, to enhance R&D efficiency Define the technical architecture for the AI application platform, covering LLM integration, agent orchestration, RAG, function calling, and multi-agent collaboration Plan AI middleware (vector databases, model gateways, prompt management, and evaluation and monitoring systems) Drive the implementation of AI to enhance R&D efficiency (code generation, intelligent testing, intelligent operations and maintenance, fault diagnosis, etc.) Lead the API-ization and platformization of AI capabilities to lower the barrier to entry for business teams Establish technical standards and specifications (including AI engineering guidelines) to drive technology implementation and ensure code quality and system performance Drive improvements in R&D efficiency, optimize development processes, and promote cost optimization and resource utilization at the technical level Participate in tackling technical challenges, resolving system bottlenecks, and providing innovative solutions Guide team members in enhancing their technical capabilities, and organize technical knowledge-sharing sessions Establish a continuous learning mechanism for cutting-edge AI technologies to drive the team’s skill development What you'll need Bachelor’s degree or higher in Computer Science, Software Engineering, or a related field At least 5 years of backend development experience, including at least 3 years of Go development experience; prior experience in a technical lead or architect role Hands-on experience building high-concurrency systems, with a deep understanding and practical experience with microservices architecture Proficiency in distributed system design principles, and familiarity with common system architecture patterns and best practices Extensive practical experience with caching design, database performance optimization, and middleware such as message queues In-depth understanding of the capabilities and engineering practices of mainstream LLMs (GPT, Claude, Llama, Qwen, etc.) Practical experience implementing AI application architectures such as RAG and Agents Strong communication skills and a collaborative spirit, with the ability to drive the comprehensive implementation of technical requirements across teams Strong problem-solving skills and the ability to independently tackle complex technical challenges 岗位职责： 持续开发升级架构组基础服务（API 网关、服务注册发现、负载均衡等），确保系统稳定性和可扩展性 为公司各种活动和业务场景提供高可用、高并发、低延迟的技术方案，支持业务快速迭代 持续建设公司级别技术基建，包括公共开发工具、代码工具包、中间件等，提升研发效率 制定 AI 应用平台技术架构，涵盖 LLM 集成、Agent 编排、RAG、Function Calling、多 Agent 协作等 规划 AI 中间件（向量数据库、模型网关、Prompt 管理、评估与监控体系） 推动 AI 在研发效能方向的落地（代码生成、智能测试、智能运维、故障诊断等） 主导 AI 能力的 API 化与平台化，降低业务团队接入门槛 建立技术标准与规范（含 AI 工程规范），推动技术落地，确保代码质量和系统性能 推动研发效能提升，优化开发流程，推动技术层面的成本优化和资源利用率提升 参与技术难题攻关，解决系统瓶颈问题，提供创新性解决方案 指导团队成员进行技术能力提升，组织技术分享和知识传递 建立 AI 前沿技术的持续学习机制，推动团队能力升级 任职要求： 计算机科学、软件工程或相关领域本科及以上学历 5 年以上后端开发经验，3 年以上 Golang 开发经验，曾担任技术专家或架构师职位 有实际的高并发系统建设经验，对微服务架构有深入的理解和实践 精通分布式系统设计原则，熟悉常见的系统架构模式和最佳实践 对缓存设计、数据库性能优化、消息队列等中间件有丰富的实践经验 深入理解主流 LLM（GPT、Claude、Llama、Qwen 等）的能力边界与工程化实践 有 RAG、Agent 等 AI 应用架构的实际落地经验 具备良好的沟通能力和团队协作精神，能够跨团队推动技术需求的全面落地 具有较强的问题分析和解决能力，能够独立处理复杂技术挑战 加分项 有 Harness Engineering、模型评估体系建设经验 熟悉至少一种主流云平台（AWS / GCP / Azure）的 AI 相关服务 有 Web3 / 金融 / 交易等领域 AI 应用经验 AI 开源社区有贡献或技术影响力 If you are ambitious and believe that digital assets could be the next financial and technological revolution, please apply!

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