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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading pre-sales organizations and technical sales for complex B2B environments, with a strong focus on architecting end-to-end solutions and driving commercial momentum through effective collaboration with cross-functional teams.
Highest-signal resume keywords
Pre-Sales Leadership ExperienceTechnical Sales ExpertiseSolutions Architecture DevelopmentNVIDIA Architecture FluencyKubernetes GPU Operators
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Architecting End-to-End SolutionsOperating Production ML WorkloadsPerformance BenchmarkingCapacity PlanningTechnical Quality StandardsStructured Qualification (MEDDPICC)Discovery Frameworks DevelopmentRFP Response LibrariesTCO ComparisonsMulti-Year Deal Structures
Soft Skills
CoachingTeam LeadershipInfluencing Roadmap PrioritizationCollaboration
Tools & Technologies
NVIDIA DGXNVIDIA HGXNVIDIA MGXKubernetesSlurmInfiniBandNVLinkSpectrum-X EthernetRDMA/RoCEHigh-Throughput Storage Systems
Industry Keywords
AI PipelinesCloud PartnershipsHyperscalerAccelerated-Hardware VendorB2B Environments
Tech Stack
Tools & technologiesCloudKubernetesNode.js
About the role
Key responsibilities & impact- Build and scale the global pre-sales organization
- Hire, coach, and retain Solutions Architects and Field Engineers
- Establish the global pre-sales operating model as headcount and deal volume scale
- Build reusable discovery frameworks, reference architectures, TCO and benchmark models, POV playbooks, and RFP response libraries
- Set technical quality standards and run enablement on GPU architecture, high-speed fabrics, and container orchestration
- Partner with Account Executives as the technical executive on strategic enterprise opportunities
- Lead technical sales for long-cycle opportunities of 6–18+ months and multi-million-dollar ACV/TCV
- Execute structured qualification using MEDDPICC or equivalent
- Architect end-to-end solutions across compute, networking, storage, and orchestration
- Deliver sizing, capacity plans, and TCO comparisons against public clouds and self-built alternatives
- Design and drive POVs and POCs, define success criteria, run performance benchmarks, and convert results into commercial momentum
- Feed product, capacity, and feature requirements to product management, engineering, and supply planning teams
- Partner with the NVIDIA field ecosystem on cloud partnerships, reference architectures, and joint pursuits
- Influence roadmap prioritization, packaging, and go-to-market strategy based on field feedback
Requirements
What you’ll need- Pre-sales leadership experience at a NeoCloud, hyperscaler AI organization, or accelerated-hardware vendor
- Proven track record leading technical sales in complex B2B environments
- Experience with multi-year committed-capacity or reserved-capacity deal structures preferred
- Track record of hiring, developing, and leading Solutions Architecture or Field Engineering teams
- Technical depth to lead complex architecture and sales discussions
- Hands-on experience standing up or operating production ML workloads, including distributed training and multi-node inference
- Deep understanding of performance bottlenecks across interconnect, memory bandwidth, I/O, and cluster scheduling
- Fluency across NVIDIA Hopper and Blackwell architectures, including H100/H200, GB200 NVL72, and B200
- Experience with NVIDIA reference systems including DGX, HGX, and MGX
- Deep understanding of NVLink/NVSwitch, InfiniBand, Spectrum-X Ethernet, RDMA/RoCE, and DPUs
- Strongly preferred: Kubernetes GPU operators and device plugins, KubeVirt, Metal3/Ironic bare-metal provisioning, and Slurm
- Familiarity with high-throughput parallel/object storage systems for AI pipelines
- Familiarity with data center physical constraints including power, cooling, and rack density
Benefits
Comp & perks- Remote work
- Opportunity to work with open source AI infrastructure, Kubernetes, GPU orchestration, and sovereign cloud technologies
- Collaboration with NVIDIA field ecosystem and participation in joint pursuits