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Strong employer brand, metro location, and senior title increase competition despite specialized Kubernetes/AI infra requirements.
Platform and cloud engineering skills transfer across industries, though regulated healthcare experience moderately increases preference.
Explicit 10+ years, leadership requirement, and mandatory Kubernetes/AWS/AI-infra skills create high shortlisting strictness.
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Lead and manage a distributed Platform Engineering team across India responsible for a large-scale, cloud-native compute platform on AWS and Kubernetes hosting AI/ML applications.
Own platform strategy, roadmap, and execution ensuring security, scalability, reliability, 24/7 operational excellence, and continuous evolution aligned with business and developer needs.
Provide technical leadership, architectural guidance, and drive stakeholder collaboration to improve developer experience through self-service capabilities, process standardization, and risk management.
10+ years experience in Platform Engineering or Site Reliability Engineering.
2+ years experience leading and developing engineering teams focused on AI infrastructure or Platform as a Service (PaaS).
Technical expertise in Kubernetes platform management (AWS EKS, Azure AKS, or GCP GKE), AI/ML ops, security compliance, and production operations of complex distributed platforms.
Work Experience Required: 10+ years; Location: distributed team across India; Notice Period: Not explicitly mentioned in the JD.
Experienced leader able to balance technical strategy, execution, and people management in large-scale, cloud-native platform environments supporting AI/ML workloads.
Proficient in operating multi-tenant, distributed compute platforms with knowledge of cloud-native architectures, observability, CI/CD, GitOps, and Infrastructure as Code practices.
Capable of engaging cross-functional stakeholders including engineering, architecture, security, and business teams to deliver platform adoption and engineering standards in a globally distributed setting.