About the role
We are seeking a skilled DevOps Engineer with 5-7 years of experience in designing, implementing, and managing cloud infrastructure, CI/CD pipelines, and DevOps practices across Azure/AWS/GCP. The ideal candidate will have strong expertise in infrastructure automation, containerization, cloud-native architectures, monitoring, security, and platform reliability. The role involves working closely with development, data, AI/ML, and cloud teams to build scalable, secure, and highly available enterprise platforms.
Responsibilities:
- Design, implement, and manage cloud infrastructure on Azure/AWS/GCP.
- Build and maintain CI/CD pipelines for application, data, and AI/ML deployments.
- Automate infrastructure provisioning using Infrastructure as Code (IaC) tools.
- Deploy and manage containerized applications using Docker and Kubernetes.
- Configure monitoring, logging, alerting, and observability frameworks.
- Implement cloud security best practices, access controls, governance, and compliance standards.
- Optimize cloud resource utilization, performance, scalability, and operational costs.
- Support production deployments, incident management, troubleshooting, and root cause analysis.
- Collaborate with Development, Data Engineering, AI/ML, and Security teams to ensure reliable and efficient deployments.
- Develop reusable automation frameworks, deployment templates, and operational runbooks.
Requirements:
- Bachelor's degree in computer science, information technology, engineering, or a related field.
- 5-7 years of hands-on experience in DevOps, cloud engineering, or site reliability engineering.
- Experience implementing enterprise-scale CI/CD and cloud automation solutions.
- Cloud certifications (Azure, AWS, or GCP) preferred.
- A hands-on DevOps engineer with strong expertise in Azure, AWS, and/or GCP, capable of building secure, scalable, and automated cloud platforms while enabling fast, reliable delivery of applications, data, and AI solutions at enterprise scale.
Cloud Platforms:
- Microsoft Azure and/or AWS and/or Google Cloud Platform.
- Compute, Storage, Networking, IAM, and Security Services.
- Cloud Architecture and High Availability Design.
DevOps and Automation:
- Azure/AWS/GCP DevOps, GitHub Actions, Jenkins, GitLab CI/CD.
- Infrastructure as Code (Terraform, ARM, Bicep, CloudFormation).
- Shell Scripting, Python, PowerShell.
Containers and Orchestration:
- Docker.
- Kubernetes (AKS, EKS, GKE).
- Helm Charts.
- Container Registry Management.
Monitoring and Security:
- Azure Monitor, Application Insights
- CloudWatch, Stackdriver/Google Monitoring.
- Prometheus, Grafana, and ELK Stack.
- Vulnerability Management and Security Automation.
AI/ML and Data Platform Exposure (Preferred):
- Azure ML, AWS SageMaker, and Vertex AI.
- Databricks, Synapse, Snowflake.
- MLOps and Model Deployment Pipelines.