Senior Cloud Infrastructure Specialist

1 week ago

Barcelona, Philippines beBeeSenior Full time $100,000 - $150,000

We are seeking a seasoned professional to own the creation, updating, and deletion of model pools in our cloud-based infrastructure. The successful candidate will be responsible for provisioning and decommissioning across Dev, Test, and Production environments, implementing timely security patches for all model pools, ensuring compliance in regulated environments, quota monitoring, and dynamic scaling to optimize resource allocation.


Key Responsibilities
  • Model Pool Management: Create, update, and delete model pools to ensure smooth operation of our cloud-based infrastructure.
  • Provisioning and Decommissioning: Provision and decommission resources across Dev, Test, and Production environments.
  • Security Patch Management: Implement timely security patches for all model pools to prevent vulnerabilities.
  • Compliance: Ensure compliance with regulatory requirements in regulated environments.
  • Quota Monitoring and Scaling: Monitor quotas and dynamically scale resources to optimize resource allocation.

Required Skills and Qualifications
  • C# and .NET Proficiency: Strong proficiency in C# and .NET for automation and service development.
  • Geneva Actions Experience: Hands-on experience with Geneva Actions for resource lifecycle automation.
  • Azure Data Explorer and Kusto Query Language (KQL) Expertise: Experience with Azure Data Explorer and KQL for monitoring and analytics.
  • Azure DevOps Knowledge: Familiarity with Azure DevOps for CI/CD pipeline implementation.
  • Cloud Platform Understanding: Solid understanding of model lifecycle, scaling, and quota management in cloud environments.
  • Security Patch Management Experience: Experience in security patch management in regulated or government cloud environments.

Bonus Qualifications
  • AI/ML Model Deployment Experience: Experience with AI/ML model deployment and inference workloads.
  • Large-Scale Cloud Platforms Expertise: Experience working with large-scale cloud platforms such as Azure.
  • Performance Tuning and Cost Optimization: Understanding of performance tuning and cost optimization for cloud-based ML services.

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