Senior DevOps Engineer - Huawei Cloud | AI Deployer
New
J
JobgetherCloud infrastructure
Based in BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- DockerKubernetesMicrosoft AzureCI/CDTerraform
Requirements
- Practical experience with Huawei Cloud services, including CCE, ECS, OBS, FunctionGraph, LTS, and IAM.
- Experience with Microsoft Azure services such as AKS, Virtual Machines, App Services, and Azure Monitor.
- Strong experience with Terraform for infrastructure provisioning and configuration management.
- Proficiency with Docker and Kubernetes in production or enterprise environments.
- Experience building, maintaining, and troubleshooting Azure DevOps Pipelines; knowledge of Huawei CodeArts.
- Practical experience managing deployments, implementing rollback procedures, and recovering from infrastructure or application failures.
- Knowledge of logging, monitoring, alerting, and diagnosing issues across cloud environments.
- Understanding of cloud security principles, identity and access management, and automated environment controls.
- Experience with databases such as GaussDB, PostgreSQL, SQL Server, MongoDB, or Azure Cosmos DB is a plus.
- Familiarity with Kafka, RabbitMQ, Azure Service Bus, or Huawei Distributed Message Service (DMS) is a plus.
- Experience with SonarQube, Gitflow, and DevSecOps practices is a plus.
- Huawei Cloud, Microsoft Azure, or Kubernetes certifications are a plus.
Responsibilities
- Provision, configure, and maintain cloud resources across Huawei Cloud and Microsoft Azure.
- Manage Kubernetes clusters and containerized workloads using Huawei Cloud CCE and Azure Kubernetes Service (AKS).
- Implement and maintain Infrastructure as Code using Terraform.
- Develop and optimize delivery workflows using Azure DevOps Pipelines and Huawei CodeArts.
- Define and automate quality gates, security checks, and compliance validations throughout the deployment lifecycle.
- Coordinate deployments, release management, and production rollouts while maintaining reliability and traceability.
- Implement rollback and recovery mechanisms to minimize service disruption.
- Configure logging, monitoring, alerting, and operational visibility.
- Implement identity and access management controls, permissions, and infrastructure security policies.
- Integrate AI-supported engineering and deployment workflows into CI/CD pipelines.
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