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.