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Medium: metro location, common engineering manager title, but seniority and niche platform requirements limit applicants.
High: requires specialized storage, hybrid cloud, AIOps and large-scale platform expertise, limiting transferability.
High: explicit 15+ years and multiple mandatory platform, cloud, storage, and AIOps skills.
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Lead design and development of Manageability solutions for a large-scale hybrid AI data platform.
Build and oversee cloud-native, API-first, AI/ML-powered systems focused on scalability, reliability, and automation.
Own team leadership, engineering best practices, infrastructure management, and delivery of unified management platform at petabyte scale.
15+ years of software engineering experience with distributed systems or cloud platforms.
5+ years in technical leadership or management roles.
Proven experience in building large-scale platform management or infrastructure systems.
Experience with APIs, microservices, infrastructure-as-code, hybrid cloud/OnPrem deployments, and AI/ML applied to operational analytics.
Experienced leader of high-performing teams delivering production-grade, enterprise-scale distributed systems.
Strong background in distributed systems architecture, cloud-native technologies, and AI-driven operational automation.
Skilled in establishing engineering best practices, driving automation-first principles, and aligning platform capabilities with business/customer needs.