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, Open. Stack, 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, Model. Arts, 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