AI Engineer developing scalable AI and data platforms on Microsoft Azure. Collaborating closely with application, data, and machine learning teams to ensure efficient deployment and monitoring.
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.
Requirements
3 to 6 years of relevant experience in AI platform enablement, DevOps, Cloud Engineering, or related roles
Proven experience supporting production workloads on Microsoft Azure
Hands-on exposure to CI/CD automation, container platforms, and cloud-native architectures
Bachelor's degree required (Engineering, Computer Science, or related discipline preferred)
Technical Skills
Azure DevOps Pipelines and GitHub Actions
YAML-based CI/CD automation
Azure Kubernetes Service (AKS)
Docker and Helm
Azure App Service, Virtual Machines, VNet
Azure Data Lake Storage (ADLS Gen2)
Azure SQL Database
Azure Container Registry (ACR)
Azure Key Vault
Azure Data Factory and Databricks
Azure Monitor and Log Analytics
Bash, PowerShell, Python (basic)
Professional Skills
Strong problem-solving and analytical mindset
Excellent collaboration and stakeholder communication skills
Experience working in Agile / Scrum teams
High ownership, accountability, and execution focus
Ability to work across DevOps, data, and AI engineering domains
Continuous improvement and automation-first mindset
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