Senior DevOps Engineer
New
IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- English
- Experience
- Minimum of 3 years
- Required Skills
- AWSDockerGCPKubernetesAzureCI/CDTerraformGitHub Actions
Requirements
- Minimum of 3 years of experience in DevOps, Cloud Infrastructure, Site Reliability Engineering, or related disciplines.
- Strong hands-on expertise with at least one major cloud platform, including AWS, GCP, and/or Microsoft Azure.
- Solid experience with containerization and orchestration technologies such as Docker and Kubernetes.
- Proven ability to design and manage CI/CD pipelines using GitHub Actions or similar automation tools.
- Practical experience with Infrastructure as Code frameworks, particularly Terraform.
- Strong understanding of networking concepts, including VPCs, cloud security groups, and cloud-native services.
- Experience managing production-grade environments with a focus on scalability, reliability, security, and performance optimization.
- Knowledge of monitoring, logging, and observability platforms and best practices.
- Familiarity with GPU infrastructure and machine learning workload deployment is considered a strong advantage.
- Excellent troubleshooting, analytical thinking, and problem-solving capabilities.
- Strong communication skills in English, with the ability to collaborate effectively across distributed teams.
Responsibilities
- Design, build, and maintain scalable cloud infrastructure across AWS, Google Cloud Platform, and Azure environments.
- Develop and optimize CI/CD pipelines to enable efficient code integration, testing, and automated deployments.
- Implement Infrastructure as Code practices using tools such as Terraform to ensure consistency, repeatability, and scalability.
- Containerize applications and manage orchestration platforms using Docker and Kubernetes.
- Build and operate monitoring, logging, observability, and alerting frameworks to ensure high availability and proactive issue resolution.
- Manage secure, private, and VPC-isolated enterprise deployments with strong emphasis on security, compliance, and audit readiness.
- Collaborate with machine learning teams to deploy and scale AI training and inference workloads, including GPU-enabled infrastructure when required.
- Partner with engineering and security stakeholders to improve infrastructure resilience, operational processes, and cloud cost efficiency.
- Maintain technical documentation and establish best practices for infrastructure operations and platform management.
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