DevOps Engineer

DevOps Engineer (AI/ML)
Location : Remote
Experience : 5yrs
*position*
: Contract
We are looking for a skilled DevOps Engineer with extensive experience in both AWS and Azure cloud environments, specifically focused on AI/ML services. The ideal candidate will have hands-on experience in building, deploying, and managing infrastructure to support machine learning pipelines and model deployments at scale.

Responsibilities

• Cloud Management : Design, deploy, and manage cloud resources on Azure and AWS, including virtual machines (VMs), virtual networks, and serverless services.
• AI/ML Operations : Develop and maintain automated machine learning pipelines, data processing tools, and model deployment strategies using services like AWS SageMaker and Azure Machine Learning.
• Replication and Migration : Plan and execute the replication of serverless resources and architectures from AWS to Azure, ensuring best practices and seamless transitions.
• Containerization : Utilize Docker and Kubernetes (EKS for AWS, AKS for Azure) to manage and scale AI models in a containerized environment.
• Infrastructure as Code (IaC) : Create and maintain IaC using Terraform to provision and manage Azure resources.
• CI/CD : Develop and manage CI/CD pipelines in Azure DevOps for automated deployments and release strategies.
• Messaging and Events : Manage messaging and event-driven architectures using Azure Service Bus, Event Grid, and Event Hubs.
• Database Administration : Administer Azure Databases (SQL, Cosmos DB, etc.) and optimize their performance.
• API Management : Develop, maintain, and manage APIs with Azure Functions, Logic Apps, and Azure API Management.
• System Administration : Administer web servers like Apache and Nginx.
• Troubleshooting : Diagnose and resolve issues related to cloud resources, network connectivity, and application performance.
• Collaboration : Work closely with development, operations, and architecture teams to ensure seamless integration and operational excellence.
• Security : Implement security best practices, including setting up Single Sign-On (SSO) using Azure Active Directory and managing data in Azure Blob Storage.

Required Skills & Experience

• Cloud Platforms : In-depth experience with AWS and Azure, particularly with AI/ML services.
• Containerization : 3+ years of hands-on experience with Docker and Kubernetes (EKS and AKS).
• IaC : Expert-level proficiency with Terraform for resource provisioning in Azure environments.
• Serverless : Strong expertise in Azure Serverless services (Azure Functions, Logic Apps, Event Grid).
• CI/CD : Advanced skills in Azure DevOps, including build and release automation.
• Replication/Migration : Proven experience in replicating and migrating resources between cloud environments (specifically AWS to Azure).
• Networking : Deep knowledge of designing and managing Azure Virtual Machines and Virtual Networks.
• Databases : Experience administering Azure Databases like SQL and Cosmos DB.
• Web Servers : 3+ years of hands-on experience with Apache and Nginx.
• APIs : Proficiency in managing APIs with Azure API Management.
• Storage : Experience with Azure Blob Storage for data management.
• Other : Knowledge of Azure OpenAI for developing intelligent applications and expertise with Azure Notification Hubs is a plus.

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