Cloud Engineer

Department: Transmission Network，Internet Network and Cloud Infrastructure Support & Maintenance

In this position, you will:

• Responsible for the deployment, delivery, capacity expansion, upgrade, migration/cutover, and O&M support of general computing and AI cloud projects, ensuring projects go live on schedule and operate stably.
• Handle the installation, configuration, resource management, performance optimization, and troubleshooting of IaaS infrastructure, including compute, virtualization, network, storage, and GPU resources.
• Manage the deployment, upgrade, and O&M of PaaS components, including Kubernetes, databases, caching, message middleware, API gateways, big data, and AI platforms.
• Oversee the delivery and O&M of AI computing clusters, covering heterogeneous computing, high-performance networking, distributed storage, resource scheduling, multi-tenant isolation, and auto-scaling.
• Build and maintain cloud platform systems for monitoring, logging, alerting, inspection, capacity management, backup/recovery, disaster recovery, and emergency response.
• Conduct performance stress testing, fault localization, and root cause analysis for cloud platforms; resolve complex technical issues in compute, network, storage, container, and AI training/inference processes.
• Drive the standardization and automation of delivery and O&M processes; develop implementation plans, operation manuals, emergency response plans, acceptance materials, and technical knowledge bases
• Collaborate with product and enterprise delivery teams to conduct requirement analysis, solution reviews, technical validation, customer training, and on-site technical support.

To be successful in this position, you should meet the following requirements:

• Bachelor’s degree or above in Computer Science, Software Engineering, Information Systems, Communication Engineering, or related fields.
• 3+ years of experience in cloud platform and infrastructure delivery/O&M, with end-to-end implementation experience in private cloud projects.
• Proficient in at least one mainstream cloud platform or private cloud product, such as Huawei Cloud, Alibaba Cloud, AWS, Azure, OpenStack, Apsara Stack, or Huawei Cloud Stack.
• Deep understanding of IaaS technologies, including servers, virtualization, bare metal, VPC, routing, load balancing, VPN, and block, file, and object storage.
• Proficient in Kubernetes architecture and O&M, including cluster deployment, node management, CNI, CSI, Ingress, container runtimes, and high-availability configurations.
• Familiar with the deployment and O&M of databases, caching, message middleware, API gateways, big data platforms, and DevOps/CI/CD toolchains.
• Familiar with heterogeneous computing (e.g., GPUs), RDMA/RoCE high-performance networking, distributed storage, and resource scheduling. Prior experience in AI computing centers or large-scale GPU clusters is preferred.
• Understanding of AI model training, inference, and basic MLOps workflows. Prior experience with Ascend, CUDA, PAI, ModelArts, or similar AI platforms is preferred.
• Solid capabilities in monitoring/alerting, capacity planning, performance stress testing, backup/disaster recovery, root cause analysis, and emergency response for critical failures.
• Cloud-related certifications, such as Huawei Cloud Solution Architect, Alibaba Cloud Solution Architect, or AWS Solutions Architect, are highly preferred.
• Strong customer communication, technical documentation, and on-site troubleshooting skills, with the ability to adapt to project delivery and necessary business travel. Certifications in cloud computing or Kubernetes are preferred.
  

When you work:

· 5 days work

· 8 hours/day

What you enjoy:

· Discretionary bonus

· Life insurance

· Medical insurance

· Education subsidies

· Birthday gift

· Birthday leave

· Staff discount