Senior AI Cluster Automation Lead (Bare-Metal)

Lenovo

Morrisville (NC)

Presencial

USD 180.000 - 240.000

Tempo integral

Há 3 dias

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Resumo da vaga

Lenovo is seeking an experienced Development Engineering Manager to lead the technical strategy, architecture, integration, and development of AI cluster management, deployment, validation, and automation software. You will drive bare-metal AI/HPC infrastructure bring-up, provisioning, validation, and lifecycle management across production clusters.

You will collaborate with NVIDIA/AMD partners, solution architects, and GPU/server teams to deliver scalable, reliable deployment workflows,

Qualificações

Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.
8+ years of experience in software engineering, infrastructure engineering, cluster management, distributed systems, AI/HPC infrastructure, or related areas.
Experience leading technical projects and/or engineering teams.
Hands‑on experience deploying, managing, and troubleshooting Linux-based bare‑metal infrastructure in AI, HPC, data center, or large‑scale distributed computing environments.
Strong software architecture and system-design skills, including modular integration, API contracts, reuse-versus-build decisions, and component lifecycle management.

Responsabilidades

Own the technical roadmap and software architecture for a cluster-validation solution built on open-source AI infrastructure.
Lead ACTOR development as an integration and workflow layer, prioritizing hardware enablement, deployment automation, validation, and customer-specific capabilities.
Lead software architecture and automation for bare-metal cluster deployment, hardware validation, infrastructure qualification, cluster bring-up, and acceptance testing.
Define modular, API-driven architectures spanning discovery, provisioning, configuration, observability, validation, and lifecycle management.
Establish engineering standards, design reviews, automated integration testing, and release practices.
Drive technical decisions around deployment repeatability, validation coverage, observability, and lifecycle-management automation.