Site Reliability Engineer

工作职责

• 在服务上线前提供系统设计咨询、上线评审、可靠性评审和生产就绪检查。
• 持续提升云平台和基础设施的可靠性、可扩展性、可观测性、成本效率、简洁性和可维护性。
• 建设和维护基础设施自动化、监控告警、故障响应和可靠性工程相关能力。
• 使用 AI 工具提升 SRE 工作效率，包括故障分析、告警降噪、日志分析、自动化、文档生成和运维效率优化。
• 与研发团队协作，识别系统可靠性风险，推动架构优化和长期基础设施改进。

任职要求

• 至少 2 年大规模分布式系统、基础设施、平台工程或 SRE 相关经验。
• 熟悉 AWS、GCP 等云服务。
• 熟悉日志、监控、链路追踪和可观测性工具，如 CloudWatch、Elasticsearch/Kibana、Prometheus/Grafana 或类似平台。
• 熟悉至少一种 IaC 或自动化工具，如 Ansible、Terraform、CloudFormation 或类似工具。
• 熟悉 Kubernetes 和常见开源基础设施平台; 有 Hadoop 或大数据平台经验优先。
• 了解故障管理、变更管理、容量规划、性能排查和生产环境运维。
• 对 AI 工具有兴趣，愿意使用 AI 提升监控、故障处理、自动化、文档和基础设施运维效率。
• 具备良好的沟通协作能力、责任心、问题解决能力和细节意识。

Responsibilities

• Support services before they go live through system design consulting, launch reviews, reliability reviews, and production readiness checks.
• Improve system reliability, scalability, observability, cost efficiency, simplicity, and maintainability across cloud and infrastructure platforms.
• Build and maintain infrastructure automation, monitoring, alerting, incident response, and reliability engineering practices.
• Use AI tools to improve SRE workflows, including incident analysis, alert noise reduction, log analysis, automation, documentation, and operational efficiency.
• Work closely with engineering teams to identify reliability risks, improve architecture, and drive long-term infrastructure improvements.

Requirements

• At least 2 years of experience in large-scale distributed systems, infrastructure, platform engineering, or SRE roles.
• Familiar with cloud services such as AWS and GCP.
• Experience with logging, monitoring, tracing, and observability tools such as CloudWatch, Elasticsearch/Kibana, Prometheus/Grafana, or similar platforms.
• Experience with at least one IaC or automation tool, such as Ansible, Terraform, CloudFormation, or similar tools.
• Experience with Kubernetes and common open-source infrastructure platforms; Hadoop or big data platform experience is a plus.
• Basic understanding of incident management, change management, capacity planning, performance troubleshooting, and production operations.
• Interest in AI tools and willingness to use AI to improve monitoring, incident handling, automation, documentation, and infrastructure operations.
• Good communication and coordination skills, strong sense of ownership, problem-solving mindset, and attention to detail.