Head of Solutions Architecture – AI Infrastructure
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Job Description
Head of Solutions Architecture leading Mirantis’ pre-sales organization for Kubernetes-native AI infrastructure. Architecting GPU cloud solutions and driving strategic enterprise deals.
Responsibilities:
- Build and scale the global pre-sales organization and operating model
- Hire, coach, and retain Solutions Architects and Field Engineers
- Develop reusable discovery frameworks, reference architectures, TCO/benchmark models, POV playbooks, and RFP response libraries
- Establish technical quality standards and enablement for 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 compute, networking, storage, and orchestration solutions
- Deliver sizing, capacity plans, and TCO comparisons against public clouds and self-built alternatives
- Design and drive POVs/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
- Partner with the NVIDIA field ecosystem on reference architectures and joint pursuits
- Influence roadmap prioritization, packaging, and go-to-market strategy through field feedback
Requirements:
- Proven track record leading technical sales in complex B2B environments
- Experience with multi-year committed-capacity or reserved-capacity deal structures is ideal
- Track record of hiring, developing, and leading Solutions Architecture or Field Engineering teams
- Technical depth to lead complex deals while scaling others
- 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: DGX, HGX, and MGX
- Deep understanding of NVLink/NVSwitch, InfiniBand, Spectrum-X Ethernet, RDMA/RoCE, and DPUs
- Pre-sales or infrastructure leadership experience at a NeoCloud, hyperscaler AI organization, or accelerated-hardware vendor strongly preferred
- Hands-on experience with 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:
- Professional development and training
- Attend conferences and working groups
- Company outings, happy hours, hackathons, and tech talks
- Competitive compensation package with a strong benefits plan
- Work with exceptionally passionate, talented and engaging colleagues
- Be a part of cutting-edge, open-source innovation
- Young-company environment valuing openness, collaboration, risk-taking, and continuous growth
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