Educational Qualification : Engineering & preferably from a premier institute.
Responsibilities
Work closely with development, operations, and other cross-functional teams to foster collaboration and effective communication.
Possess extensive expertise in navigating and contributing to software development environments based on Linux/Unix systems.
Demonstrate hands-on experience on AI/ML workload integrations and executions.
Implement and maintain Kubernetes clusters, showcasing a deep understanding of orchestration scaling, and resource management.
Leverage Certified Kubernetes Administrator (CKA) credentials to ensure best practices in Kubernetes administration, troubleshooting, and performance tuning.
Work seamlessly in a multi-cloud environment, specifically AWS and Azure.
Execute hands-on development and deployment of microservices and containerized applications.
Manage databases within Kubernetes clusters and establish continuous delivery pipelines using tools like Jenkins, GitLab CI/CD, and Travis CI.
Deliver high quality, scalable, and resilient solutions that are documented and thoroughly tested.
Employ scripting for automation and demonstrate proficiency in building and managing systems, infrastructure, and applications through automation using infrastructure as code, with notable experience in Terraform.
Possess an understanding of operational concepts and tooling, including monitoring platforms such as Grafana or Nagios, log aggregation solutions like Splunk, and distributed tracing.
Stay current with the latest trends, tools, and best practices in Cloud and DevOps.
Requirements
Minimum 2+ years of experience in any of the roles -DevOps, build release, integration, configuration engineer.
2 + years of strong experience working with Linux/Unix software development environments.
Solid practical exposure to integrating and executing AI/ML workloads.
2+ year experience in Docker and Kubernetes with practical expertise (holding CKA Certification), and familiarity with Helm.
Expertise in networking, security, and cloud platforms (AWS, Azure, GCP, etc.