Global Resolution Engineer (Remote US)

Role overview Take ownership of high-impact customer escalations that span applications, compute, networking, storage, and cloud infrastructure. The role focuses on finding underlying causes, delivering durable fixes, and turning individual incidents into improvements that reduce risk across a wider customer base. It also has a specialist focus on large GPU environments built around partner reference architectures, with some work outside regional business hours.

Responsibilities - Lead complex incidents from initial investigation through resolution, including direct participation in customer calls during critical events. - Trace faults across the full system stack and across product or vendor boundaries. - Identify recurring defects and assess their potential impact across customers and software versions. - Resolve issues directly where possible; for engineering fixes, provide reproducible evidence and a clear root-cause hypothesis. - Maintain technical advisories and knowledge articles, and turn recurring issues into product, process, and diagnostic improvements. - Improve support tools, mentor and train customer success engineers, and participate in a 24/7 on-call rotation. - Advise on GPU cloud environments, benchmarks, and joint troubleshooting with partner engineers.

Requirements - At least ten years in advanced customer-facing technical support, sustaining engineering, site reliability, or systems engineering; a relevant degree or equivalent practical experience. - Proven ability to resolve complex distributed-systems issues and work with engineering teams on defects. - Deep Linux knowledge, including kernel behavior, memory, NUMA, CPU scheduling, or drivers. - Experience with distributed storage or parallel file systems and high-performance networking such as RDMA, RoCE, InfiniBand, or Ethernet. - Advanced debugging skills using tools such as perf, eBPF, gdb, and core dump or log analysis; ability to read source code and test hypotheses with data. - Strong customer communication, written English, ownership, and willingness to work flexible hours on a global team.

Nice to have - GPU and AI workload experience, including GPUDirect Storage or large accelerator environments. - Public cloud, Kubernetes, containers, virtualization, storage protocols, DPDK, UCX, or automation with Python, Bash, Ansible, or Terraform.