Bachelor's degree in Computer Science, Electrical Engineering, Systems Engineering, or equivalent technical field.
7+ years leading Customer Engineering or Solutions Architecture teams in pre-sales; demonstrated success hiring and scaling globally.
7–10+ years of hands-on pre-sales or solutions engineering experience in AI infrastructure, edge computing, datacenter, or distributed systems.
Deep expertise in GPU and AI accelerator infrastructure: NVIDIA GPU architectures, AI inference frameworks (TensorRT, ONNX, vLLM), and edge AI platforms.
Strong grounding in datacenter and edge infrastructure: compute (GPU, bare metal, virtualization), storage (SAN/NAS/Object/NVMe), networking (LAN/WAN/SD-WAN/SATCOM), and facility systems (power, cooling).
Hands-on experience with container orchestration (Kubernetes), virtualization (VMware, KVM, Hyper-V), and cloud service models (IaaS, PaaS, hybrid).
Proven ability to engage and influence C-level technical and operational leaders across global enterprise and government customers.
Willingness to travel internationally, including to remote and operationally austere field sites.

Benefits

Medical, dental, and vision (subsidized cost)
Health savings accounts (HSA), flexible spending accounts (FSA), and dependent care FSAs (DCFSA)
Retirement plan options, including 401(k) and Roth 401(k)
Unlimited paid time off (PTO)
15 paid company holidays per year

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI infrastructureedge computingdatacenterdistributed systemsNVIDIA GPU architecturesAI inference frameworksTensorRTONNXvLLMcontainer orchestration

Soft Skills

leadershipcross-functional collaborationinfluenceengagement