AI Cloud Senior DevOps Engineer
Summary
Build and automate cloud-native infrastructure for AI products, focusing on CI/CD, MLOps, Kubernetes, and GPU clusters to ensure scalable, secure, and highly available deployments.
You will operate as the backbone of deployment and infrastructure operations for AI products and platforms. You will automate CI/CD and MLOps workflows, build scalable cloud-native infrastructure, manage GPU resources, implement high availability and disaster recovery, establish observability, enforce security standards, and lead incident resolution.
Responsibilities
- Design and maintain CI/CD pipelines for applications and machine learning models
- Automate build, testing, deployment, and rollback processes
- Build and scale Kubernetes- and Docker-based cloud infrastructure
- Manage GPU clusters and specialized computing resources
- Design high-availability and disaster recovery strategies
- Provision infrastructure with Terraform, Ansible, and Helm
- Build monitoring, logging, and alerting systems
- Establish security, release, secrets management, and compliance standards
- Lead troubleshooting, root cause analysis, and remediation during incidents
Requirements
- Bachelor's degree or above in Computer Science, Engineering, or a related technical field
- 5+ years of experience in DevOps, SRE, or cloud infrastructure roles
- Expert knowledge of Linux and networking principles
- Mastery of Docker and Kubernetes
- Experience with AWS, GCP, Azure, Alibaba Cloud, or other public or hybrid cloud platforms
- Strong coding or scripting skills in Go, Python, Shell, or another major language
- Knowledge of CI/CD, Infrastructure as Code, observability, and SRE
- Experience with MLOps, model serving, GPU clusters, or large-scale distributed systems is preferred