Infrastructure Support Lead

자격 요건 · 11개

• Over 8 years in technical support, field service, or service delivery for hardware deployed at customer sites
• Over 2 years working directly with AI/ML infrastructure or accelerated compute environments
• Over 2 years leading a support or field engineering team, including engineers you did not directly employ
• Able to lead and drive debugging on a technical bridge call: read logs, reason about the hardware/software boundary, and judge whether an issue is customer configuration, firmware, or silicon
• Hands-on depth in Linux, Kubernetes, and containerized inference serving, along with Python for automation and tooling
• Able to explain technical AI concepts clearly to non-technical stakeholders, both customers and internal teams
• Experience in an externally facing customer support or service function handling both hardware faults and software or performance issues, routing each correctly — in support of external customers, not internal IT users
• Has owned major incidents for enterprise or government customers
• Experience with hardware service operations — installed base and entitlement, warranty, RMA, spares, dispatch — either end-to-end, or substantial exposure to several parts with the appetite to take on the rest
• Experience building a support process or function, not only operating one someone else designed
• Experience delivering service through third parties: helping set the standard and holding partners to it

우대 사항 · 12개

• AI/ML, HPC, or data center infrastructure background — accelerators or GPU systems, Linux, Kubernetes, inference serving
• Distributed LLM inference orchestration — vLLM disaggregated serving, NVIDIA Dynamo, llm-d, or equivalent KV-cache-aware systems
• Python and PyTorch; inference optimization and performance tuning
• Diagnosing multi-layered performance bottlenecks spanning software, middleware, networking, and infrastructure
• Data center integration experience — rack, power, cooling, and network requirements
• Has implemented ticketing and field service management systems, not just worked in them
• Experience with formal knowledge management practices such as KCS
• AI-assisted support operations — deflection, agent assist, automated triage
• Support for air-gapped or otherwise access-restricted sites
• Cross-border movement of controlled hardware for repair and replacement
• Service delivery in structurally different markets, including at least one emerging or access-restricted environment
• Experience shaping product supportability requirements before release