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Popular DevOps title, metro location, mid-level role, and broad cloud/Kubernetes requirements increase applicant density.
Core cloud, CI/CD, and Kubernetes skills are broadly transferable, though AI platform experience helps.
Multiple mandatory cloud, IaC, CI/CD, and Kubernetes skills imply strict technical screening.
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Build, automate, deploy, monitor, and operate cloud infrastructure for AI and data platforms across AWS, Azure, GCP, or equivalent.
Develop and maintain CI/CD pipelines and GitOps deployment workflows using tools like Argo CD, Flux, GitHub Actions, or Azure DevOps.
Containerize applications and manage Kubernetes workloads including Helm chart management and environment-specific configurations.
Hands-on experience with at least one major cloud platform: AWS, Azure, or GCP.
Practical experience with infrastructure as code tools such as Terraform or OpenTofu.
Experience with CI/CD tools like GitHub Actions, GitLab CI/CD, Azure DevOps, or Jenkins.
Working knowledge of Docker, Kubernetes, Helm, and Kubernetes concepts including deployments, services, ingress, secrets, namespaces, and RBAC.
Experienced engineer comfortable working directly with cloud platforms to build production-grade enterprise AI platform capabilities.
Proficient in building and supporting multi-cloud hybrid deployments and GitOps-based workflows.
Strong operational focus on containerized workload deployment and Kubernetes environment management.