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Tier-1 brand, metro location, mid-level generalist role with popular skills increases applicant competition.
Specialized GPU, AI deployment, and enterprise CSP experience limits cross-industry transferability.
Explicit 5+ years requirement and mandatory Kubernetes, Linux, Python, and GPU supportability skills make filters strict.
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Own end-to-end resolution of complex customer software issues for NVIDIA AI Enterprise across cloud and datacenter platforms, including Kubernetes and container orchestrators.
Develop and maintain Python-based automation, diagnostics, reproducible test cases, and deployment tooling to improve product readiness and support scalability.
Collaborate closely with customers and internal engineering teams to diagnose issues, drive fixes, build documentation, and support high-severity outages on call.
Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, or related field, or equivalent experience.
5+ years of system software development and troubleshooting experience including customer-facing roles.
Proficiency in Python scripting; familiarity with Bash; knowledge of Go or C++ is a plus.
Strong troubleshooting skills with understanding of networking, concurrency, OS concepts, and deep knowledge of Linux production environments.
Experience with deploying and operating NVIDIA AI Enterprise or similar GPU-accelerated AI stacks in production on-premises or cloud.
Knowledgeable in Kubernetes-based platforms including cluster operations and troubleshooting in production environments.
Strong programming skills combined with ability to develop customer-facing diagnostic tools and documentation, showing ownership of technical escalations from start to finish.