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Tier-1 brand, metro location, and broad platform skillset increase competition for qualified senior candidates.
Highly domain-specific cloud platform and leadership requirements limit cross-industry transferability.
Explicit 10+ years and 5+ years leadership plus mandatory platform stack makes filtering highly strict.
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Lead strategy, execution, and operations for cloud services supporting container, artifact, and ML model registries for NVIDIA engineering teams.
Architect, design, implement, and operate complex PaaS GPU cloud services, defining KPIs/SLAs around availability, latency, storage, reliability, and developer experience.
Mentor engineering managers and senior individual contributors; influence architecture and technical direction while representing platform strategy to senior leadership.
10+ years software engineering experience with significant ownership of cloud platforms, distributed systems, or infrastructure services.
5+ years engineering leadership experience including managing managers or leading multiple senior technical workstreams.
Bachelor's degree or equivalent experience.
Experience operating customer-facing or company-critical services with high availability, latency, throughput, data integrity, and security demands.
Experience leading teams building and operating enterprise scale distributed cloud platforms and reliability transformations including SLO adoption and stress testing.
Deep knowledge of cloud-native systems like Kubernetes, object storage, databases, event streaming, caching, container registries (Docker, Harbor, ECR, GCR, GAR).
Proven track record in growing engineering managers and senior leaders who independently own high-impact platform areas in AI infrastructure or accelerated computing domains.