Senior Cloud Capacity Specialist

1 day ago


Mandaue City, Central Visayas, Philippines beBeeCloud Full time $150,000 - $170,000
Job Title: Senior AI Capacity Engineer

Description:
Are you a highly skilled professional in AI capacity engineering? Do you have experience with model lifecycle management, scaling, and quota optimization in cloud environments? We are seeking a talented engineer to join our team as a Senior AI Capacity Engineer.

Key Responsibilities:
• Own the creation, updating, and deletion of model pools.
• Ensure accurate provisioning and decommissioning across Dev, Test, and Production environments.
• Implement and maintain timely security patches for all model pools.
• Ensure compliance in regulated environments, including US Government clouds and Microsoft internal services.
• Continuously monitor model pool usage metrics and system performance. Adjust quotas based on business demand and AI inference load to optimize resource allocation.
• Build and maintain automated workflows for lifecycle operations and monitoring. Collaborate with cross-functional teams to improve operational efficiency and governance. Analyze logs and metrics to detect anomalies, performance issues, or compliance gaps. Generate actionable insights to inform scaling, patching, and lifecycle decisions.

Required Skills & Qualifications:
• Strong proficiency in C# and .NET for automation and service development.
• Hands-on experience with Geneva Actions for resource lifecycle automation.
• Experience with Azure Data Explorer and Kusto Query Language (KQL) and Dashboard for monitoring and analytics.
• Familiarity with Azure DevOps for CI/CD pipeline implementation.
• Comfortable with Visual Studio Code or similar development environments.
• Solid understanding of model lifecycle, scaling, and quota management in cloud environments.
• Experience in security patch management in regulated or government cloud environments.
• Strong problem-solving skills and ability to work in fast-paced, dynamic environments.
• Senior engineers must have at least 5 years of relevant experience.

Preferred Qualifications:
• Experience with AI/ML model deployment and inference workloads.
• Experience working with large-scale cloud platforms such as Azure.
• Understanding of performance tuning and cost optimization for cloud-based ML services.

Tools & Technologies:
• Automation & Lifecycle Management: Geneva Actions

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