Design, build, and operate infrastructure across AWS, GCP, and Azure
Optimize cloud environments for performance, reliability, scalability, and cost efficiency
Own CI/CD pipelines from code integration through automated deployment
Implement and maintain Infrastructure as Code using Terraform or similar tools
Containerize and orchestrate services using Docker and Kubernetes
Manage GPU-enabled infrastructure for AI model training and inference workloads
Build and maintain monitoring, logging, and alerting systems
Support private, VPC-isolated enterprise deployments with strong security and audit capabilities
Collaborate with ML teams to deploy and scale training and inference workloads
Work closely with Security and Engineering teams to improve infrastructure resilience and operational excellence
Maintain infrastructure documentation and operational best practices

3+ years of experience in DevOps, Cloud Infrastructure, or Site Reliability Engineering
Hands-on experience with AWS, GCP, and/or Azure
Strong knowledge of Docker and Kubernetes
Experience building and managing CI/CD pipelines
Proficiency with Infrastructure as Code tools such as Terraform
Experience with Git, GitHub Actions, or similar automation tools
Understanding of monitoring, logging, and observability platforms
Experience managing production infrastructure with a focus on reliability and scalability
Knowledge of networking, VPCs, security groups, and cloud-native services
Familiarity with GPU infrastructure and ML workload deployment is a plus
Strong troubleshooting and problem-solving skills
Excellent written and verbal communication skills in English.

Senior DevOps Engineer

Key skills