Computer Science jobs in Singapore

The Cloud Engineer will be responsible for designing, provisioning, and maintaining Azure sandbox environments for the AI team, supporting a wide range of AI use cases from development through UAT and to production. This role will manage Azure Kubernetes Service (AKS), Azure Container Apps, and related cloud resources, ensuring robust, secure, and scalable infrastructure for AI solution deployment. The individual will collaborate closely with AI developers to enable seamless Docker-based deployments, create and manage resource groups, and build end‑to‑end CI/CD pipelines. As an infrastructure manager for the AI team, the Cloud Engineer will proactively resolve cloud resource issues, manage the cloud stack in line to architectural recommendations, and drive continuous improvement in cloud operations.

• Azure Sandbox Management:
  • Design, provision, and maintain Azure sandbox environments for multiple AI use cases.
  • Create and manage Azure resource groups, ensuring proper organization and access control.
  • Monitor and optimize sandbox resources for cost, performance, and security.
• AKS & Azure Container Apps:
  • Deploy, configure, and maintain AKS clusters and Azure Container Apps for AI workloads.
  • Ensure reliable operation and scalability of containerized applications in both sandbox and UAT environments.
  • Implement best practices for container orchestration, networking, and security.
• Dockerization & Deployment:
  • Collaborate with AI developers to build Docker base images for new use cases.
  • Manage container registries and streamline the handover of AI solutions for deployment.
  • Troubleshoot and resolve issues related to containerization and deployment.
• CI/CD Pipeline Development:
  • Design and implement end‑to‑end CI/CD pipelines for automated build, test, and deployment of AI solutions.
  • Integrate pipeline tools with Azure services to enable rapid, reliable releases.
  • Maintain pipeline health and address failures promptly.
• Cloud Resource Management & Support:
  • Act as the technical infrastructure manager for the AI engineering team.
  • Proactively identify and resolve cloud resource issues, ensuring minimal disruption to AI development and deployment.
  • Provide ongoing support and maintenance for cloud services and environments.
• Collaboration & Continuous Improvement:
  • Work closely with AI engineers, data scientists, and stakeholders to understand requirements and deliver robust cloud solutions.
  • Document processes, configurations, and troubleshooting steps for knowledge sharing.
  • Drive continuous improvement in cloud operations, automation, and security.

• Bachelor’s degree in Computer Science, Information Technology, or related field.
• 2–8 years of hands‑on experience in cloud engineering, with a focus on Azure cloud services.
• Experience managing Azure resource groups, AKS, and Azure Container Apps.
• Strong knowledge of Docker and containerization best practices.
• Proven track record in developing CI/CD pipelines for cloud‑based deployments.
• Experience supporting AI or data engineering teams is a plus.
• Cloud certifications (e.g., Azure Administrator, Azure DevOps Engineer) are advantageous.

• Technical Expertise:
  • Proficiency in Azure cloud services, including resource management, networking, and security.
  • Hands‑on experience with AKS, Azure Container Apps, and Docker.
  • Familiarity with CI/CD tools (Azure DevOps, GitHub Actions, etc.).
  • Scripting skills (PowerShell, Bash, Python) for automation.
• Collaboration & Problem‑Solving:
  • Strong troubleshooting skills and willingness to “roll up sleeves” to resolve technical issues.
  • Ability to work flexibly and adapt to changing requirements in a fast‑paced environment.
  • Excellent communication skills for collaborating with AI developers and stakeholders.

Interested candidates, who wish to apply for the above position, please send in your resume to ajay.sharma@persolapac.com

We regret to inform that only shortlisted candidates will be contacted.

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