Senior AI Capacity Engineer(India/Philippines – Remote(night shift))

4 days ago

Manila, National Capital Region, Philippines CSI Interfusion Full time ₱1,200,000 - ₱2,400,000 per year

Key Responsibilities


• Manage Model Pools with Geneva Actions

o Own the creation, updating, and deletion of model pools.

o Ensure accurate provisioning and decommissioning across Dev, Test, and Production
environments.


• Security Patch Management

o Implement and maintain timely security patches for all model pools.

o Ensure compliance in regulated environments, including US Government clouds and Microsoft
internal services.


• Quota Monitoring & Dynamic Scaling

o Continuously monitor model pool usage metrics and system performance.

o Adjust quotas based on business demand and AI inference load to optimize resource allocation
.


• Automation & Process Improvement

o Build and maintain automated workflows for lifecycle operations and monitoring.

o Collaborate with cross-functional teams to improve operational efficiency and governance.


• Monitoring & Reporting

o Analyze logs and metrics to detect anomalies, performance issues, or compliance gaps.

o Generate actionable insights to inform scaling, patching, and lifecycle decisions.

Required Skills & Experience


• 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 Dashborad 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


• Programming & Frameworks: C#, .NET


• Cloud & Data: Azure Data Explorer, KQL, Azure DevOps,Dashboard


• Development Tools: Visual Studio Code


• Automation & Lifecycle Management: Geneva Actions

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