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Strong global brand and mid-level 5–8 years profile create moderate competition.
Specialized cloud platform and AI-infrastructure expertise is moderately transferable across industries.
Explicit 5–8 years requirement plus mandatory multi-cloud, Kubernetes, IaC, and GPU/AI infrastructure skills enforce strict filters.
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Design, implement, and manage scalable, secure, and cost-efficient multi-cloud infrastructure across AWS, Azure, and GCP to support AI/ML workloads.
Build and optimize CI/CD pipelines, Infrastructure-as-Code workflows, and Kubernetes environments (EKS, AKS, GKE) with focus on governance, security, and autoscaling.
Ensure operational excellence through automation, observability (Prometheus, Grafana, ELK), compliance, security policy adherence, and mentor cross-functional teams.
5–8 years of professional experience in cloud infrastructure, platform engineering, and DevOps roles.
Hands-on expertise with cloud services and multi-cloud platforms AWS, Azure, and GCP, including compute, storage, IAM, networking, and managed services.
Strong experience with DevOps automation tools: Terraform, GitHub, GitLab, Azure DevOps, Jenkins, Docker, Kubernetes, Helm, GitOps.
Proficiency in scripting/programming languages: Python, Bash, PowerShell, and YAML.
Experienced operator in enterprise-scale, multi-cloud AI platform environments focused on secure, compliant, and highly available infrastructure.
Proven ability to architect and optimize cloud-native CI/CD pipelines and Kubernetes orchestration with deep observability and governance.
Collaborative technologist capable of mentoring teams and aligning cloud platform solutions with cross-functional engineering, product, and security stakeholders.