Head of Solutions Architecture – AI Infrastructure

This is a fully remote position, open to applicants in Kazakhstan, +1 more country.

📋 Description

• Develop and expand the global pre-sales organization and operational framework.

• Recruit, mentor, and retain Solutions Architects and Field Engineers.

• Create reusable discovery frameworks, reference architectures, TCO/benchmark models, POV playbooks, and RFP response libraries.

• Set technical quality standards and provide enablement for GPU architecture, high-speed fabrics, and container orchestration.

• Collaborate with Account Executives as the technical lead on strategic enterprise initiatives.

• Oversee technical sales for long-cycle opportunities ranging from 6 to 18+ months and multi-million-dollar ACV/TCV.

• Implement structured qualification processes using MEDDPICC or equivalent methodologies.

• Design comprehensive compute, networking, storage, and orchestration solutions.

• Provide sizing, capacity plans, and TCO comparisons against public cloud offerings and self-built solutions.

• Create and manage POVs/POCs, outline success criteria, conduct performance benchmarks, and translate results into commercial success.

• Relay product, capacity, and feature requirements to product management, engineering, and supply chain planning.

• Collaborate with the NVIDIA field ecosystem on reference architectures and joint initiatives.

• Impact roadmap prioritization, packaging, and go-to-market strategy through feedback from the field.

⛳️ Requirements

• Established history of leading technical sales in intricate B2B environments.

• Ideal candidates will have experience with multi-year committed-capacity or reserved-capacity deal structures.

• Proven success in hiring, developing, and managing Solutions Architecture or Field Engineering teams.

• Technical acumen to lead complex deals while also scaling other initiatives.

• Experience in establishing or managing production ML workloads, including distributed training and multi-node inference.

• Profound understanding of performance bottlenecks related to interconnect, memory bandwidth, I/O, and cluster scheduling.

• Proficient knowledge of NVIDIA Hopper and Blackwell architectures, including H100/H200, GB200 NVL72, and B200.

• Familiarity with NVIDIA reference systems: DGX, HGX, and MGX.

• In-depth understanding of NVLink/NVSwitch, InfiniBand, Spectrum-X Ethernet, RDMA/RoCE, and DPUs.

• Prior experience in pre-sales or infrastructure leadership at a NeoCloud, hyperscaler AI organization, or accelerated-hardware vendor is highly preferred.

• Practical experience with Kubernetes GPU operators and device plugins, KubeVirt, Metal3/Ironic bare-metal provisioning, and Slurm.

• Awareness of high-throughput parallel/object storage systems for AI workflows.

• Understanding of data center physical constraints, encompassing power, cooling, and rack density.

🏝️ Benefits

• Opportunities for professional development and training.

• Participation in conferences and working groups.

• Company outings, happy hours, hackathons, and tech talks.

• Competitive compensation package complemented by a robust benefits plan.

• Collaborate with exceptionally passionate, talented, and engaging colleagues.

• Contribute to cutting-edge, open-source innovation.

• Experience a young-company environment that values openness, collaboration, risk-taking, and continuous growth.