oracle
Manager - AI Engineering
EXL
Bengaluru, IND
Manager · 6+ years experience
Hybrid
Discovered 2 weeks ago
azureazure-data-factorybashdatabricksdockergit
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About the Role
This role partners closely with application, data, and machine learning teams to ensure AI solutions are deployed efficiently, monitored effectively, and operated at scale in an Agile environment.
Key Skills for This Role
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Responsibilities
- Key Responsibilities
- Build, manage, and optimize CI/CD pipelines using Azure DevOps and GitHub Actions for AI, data, and application workloads.
- Deploy and operate AI-enabled and data platforms on Azure Kubernetes Service (AKS) using Docker and Helm.
- Provision and manage Azure infrastructure including compute, networking, storage, and security services.
- Enable MLOps and data pipelines by supporting ETL workflows using Azure Data Factory and Databricks.
- Implement secure configuration and secrets management using Azure Key Vault.
- Monitor platform health, performance, and availability using Azure Monitor and Log Analytics.
- Conduct performance and load testing using JMeter / BlazeMeter and drive optimization actions.
- Collaborate with ML engineers to support model packaging, versioning, deployment, and monitoring in production.
- Support Agile delivery through automation, release coordination, and continuous improvement.
- Track and optimize cloud infrastructure costs across environments.
- Key Responsibilities - Build, manage, and optimize CI/CD pipelines using Azure DevOps and GitHub Actions for AI, data, and application workloads. - Deploy and operate AI-enabled and data platforms on Azure Kubernetes Service (AKS) using Docker and Helm. - Provision and manage Azure infrastructure including compute, networking, storage, and security services. - Enable MLOps and data pipelines by supporting ETL workflows using Azure Data Factory and Databricks. - Implement secure configuration and secrets management using Azure Key Vault. - Monitor platform health, performance, and availability using Azure Monitor and Log Analytics. - Conduct performance and load testing using JMeter / BlazeMeter and drive optimization actions. - Collaborate with ML engineers to support model packaging, versioning, deployment, and monitoring in production. - Support Agile delivery through automation, release coordination, and continuous improvement. - Track and optimize cloud infrastructure costs across environments.
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