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Open nowPosted 145 days ago

Senior SRE Engineer (AI Infrastructure)高级 SRE 工程师 (AI-INF-基础设施)

a9ihi0un9c/index20 open roles

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Shanghai, Chinese Mainland
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Your applicationOpen nowSenior SRE Engineer (AI Infrastructure)高级 SRE 工程师 (AI-INF-基础设施)a9ihi0un9c/index · Shanghai, Chinese Mainland
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This job: posted 145 days ago

The posting

Job Responsibilities 1.Multi-cloud Architecture Management & Business Implementation Take charge of the planning, construction and daily operation & maintenance of the company’s infrastructure on mainstream public clouds including AWS and Alibaba Cloud. Independently collaborate with business teams to deliver architecture design, resource planning, deployment & launch, and full-lifecycle management for complex business systems. 2.Stability Assurance of Kubernetes Clusters Build large-scale Kubernetes clusters, optimize their stability, conduct capacity planning and fine-tune scheduling policies. Lead containerization migration of services, and troubleshoot complex issues of cloud-native components such as network and storage. 3.O&M of AI Computing Infrastructure Ensure stable operation of large model training and inference workloads. Be proficient in driver configuration, network (InfiniBand/RoCE) and monitoring troubleshooting of heterogeneous computing servers equipped with NVIDIA GPUs, and optimize GPU resource scheduling and utilization efficiency. 4.CI/CD & Automated Pipeline Construction Design and optimize CI/CD pipelines based on GitHub Actions, GitLab CI, ArgoCD, etc. Promote the implementation of Infrastructure as Code (IaC) represented by Terraform to boost R&D delivery efficiency. 5.Observability System Development Build and optimize full-link monitoring and alerting systems with open-source tools including Prometheus, Grafana and Alertmanager. Define SLI/SLO/SLA for core businesses and establish efficient emergency response workflows for outages. 6.In-house Development of O&M Platforms Identify pain points within R&D teams, independently design and build automated O&M platforms, underlying tools or AI-Agent intelligent inspection systems using Python or Go, and eliminate repetitive toil through engineering solutions. 7.Incident Response & On-Call Rotation Participate in production on-call shifts, rapidly respond to online incidents, conduct root-cause localization, mitigate service impact and carry out post-mortem reviews, and accumulate a fault knowledge base.

岗位职责 1、多云架构管理与业务落地:负责公司在 AWS、阿里云等主流公有云上的基础设施规划、建设与日常运维;能够独立对接业务团队,完成复杂业务系统的架构设计、资源规划、部署上线及全生命周期管理; 2、K8s 集群稳定性保障:负责公司海量/大规模Kubernetes集群的构建、稳定性优化、容量规划与调度策略调优;负责服务容器化改造及网络、存储等云原生组件的疑难问题排查; 3、AI 算力基础设施运维:保障大模型训练和推理任务的稳定运行,熟悉异构算力(如 NVIDIA GPU)服务器的驱动、网络(InfiniBand/RoCE)及监控排障,优化GPU资源调度与利用率; 4、CI/CD 与自动化流水线:设计并优化持续集成与持续交付(CI/CD)流水线(如 GitHub Actions, GitLab CI, ArgoCD),推动基础设施即代码(IaC,如Terraform)的落地,提升研发交付效率; 5、可观测性系统建设:负责构建和优化全链路监控与告警体系,深入应用 Prometheus、Grafana、Alertmanager等开源工具,制定核心业务的SLI/SLO/SLA,建立高效的故障应急响应流程; 6、运维平台自研开发:深入研发团队痛点,能够使用Python或Go语言独立设计并开发运维自动化平台、底座工具或 AI-Agent 智能巡检系统,用工程化手段消除组织内的“脏活累活”(Toil); 7、应急响应与 On-Call:参与生产环境的On-Call值班,对线上突发事件进行快速响应、定位、止血与复盘,沉淀故障知识库。

Job Requirements 1.Education & Work Experience Bachelor’s degree or above in Computer Science or related disciplines, with over 5 years of working experience in SRE, DevOps or DevOps Development. Candidates with experience in AI computing clusters or large-scale Kubernetes O&M are preferred. 2.Proficiency in Public Cloud Platforms Expertise in the architecture of at least two mainstream public cloud vendors such as AWS and Alibaba Cloud. Familiar with core services including IAM, VPC, EKS/ACK, RDS, as well as cross-cloud interconnection solutions. 3.In-depth Cloud-native Expertise Thorough understanding of Kubernetes architecture and underlying principles; skilled in core components including Ingress, CoreDNS, Flannel/Calico. Capable of advanced troubleshooting, performance tuning and network packet capture at Pod and Node levels. 4.AI & Computing Infrastructure Experience (Mandatory Plus) Familiar with infrastructure support for distributed large model training (Megatron-LM, DeepSpeed) or model inference (vLLM, TensorRT-LLM). Prior experience maintaining GPU clusters with 4090, A100 or H100 is highly preferred. 5.Coding Capability Master at least one programming language between Python and Go (dual proficiency is a major plus). Possess solid algorithm fundamentals and standardized coding habits, with hands-on experience independently leading or developing medium-to-large automated O&M platforms, APIs or Kubernetes Operators. 6.Monitoring & CI/CD Competence Skilled in observability stacks including Prometheus, Grafana and ELK, able to write complex PromQL queries. Familiar with Git workflows and mainstream CI/CD tools. 7.Comprehensive Competencies Strong stress resistance, self-motivation and logical thinking. Remain calm when handling complicated online incidents, with excellent cross-team communication and collaboration skills. Preferred Qualifications 1.Possess AWS Certified DevOps Engineer – Professional or Alibaba Cloud ACE Expert certification. 2.Hold CKA (Certified Kubernetes Administrator) or CKAD certificates. 3.Practical project experience implementing AI-Agent for O&M scenarios, such as automated log analysis and self-healing based on large language models. 4.Active open-source contributor with development experience in Kubernetes, Prometheus or related cloud-native ecosystems. 任职要求 1、教育背景与经验:计算机或相关专业本科及以上学历,5年以上SRE、DevOps或运维开发经验(有AI算力集群或大规模 K8s 运维经验者优先); 2、公有云专长:熟练掌握AWS、阿里云等至少两家主流公有云厂商的架构体系,熟悉其 IAM、VPC、EKS/ACK、RDS等核心服务及跨云互联方案; 3、云原生深度掌握:深入理解 Kubernetes 架构与底层原理,熟练掌握常用组件(Ingress, CoreDNS, Flannel/Calico等),具备强大的Pod/Node级别排错、性能调优和网络抓包能力; 4、AI / 算力经验(硬性加分项):熟悉大模型分布式训练(如 Megatron-LM, DeepSpeed)或模型推理(如 vLLM, TensorRT-LLM)的基础设施支撑,有4090或 A100/H100等GPU集群稳定性保障经验者优先; 5、代码开发能力:熟练掌握Python或Go至少一门语言(同时掌握者大加分),具备良好的算法基础与代码规范,有独立主导或开发中大型自动化运维平台、API 接口、或 K8s Operator 的实战经验; 6、监控与 CI/CD 功底:熟练使用 Prometheus/Grafana/ ELK等可观测性工具,能编写复杂的PromQL;熟练掌握Git工作流及常见CI/CD工具; 7、综合素养:具备极强的抗压能力、自驱力与逻辑思维能力;面对复杂的线上故障能保持冷静,具备良好的跨团队沟通与协同能力。 加分项 1、拥有 AWS Certified DevOps Engineer - Professional 或阿里云专家认证(ACE); 2、拥有 CKA (Certified Kubernetes Administrator) / CKAD 证书; 3、拥有 AI AI-Agent 结合运维场景落地(如基于大模型的自动化日志分析、故障自愈)的实际项目经验; 4、活跃的开源社区贡献者(如有 K8s, Prometheus 等周边生态开发经验)。

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