AI Architecture AI架构师

About us

Bitget Wallet is the non-custodial crypto wallet designed to make crypto simple and secure for everyone. With over 80 million users, we bring together a full suite of crypto services, including swaps, market insights, staking, rewards, DApp exploration, and payment solutions. Supporting 130+ blockchains and millions of tokens, Bitget Wallet enables seamless multi-chain trading across hundreds of DEXs and cross-chain bridges. Backed by a $300+ million user protection fund, it ensures the highest level of security for users' assets.

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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