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Principal Solutions Architect (AI Infrastructure)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Principal Solutions Architect (AI infrastructure): Designing and delivering end-to-end GPU infrastructure solutions for demanding AI workloads with an accent on GPU compute, high-performance networking, storage, orchestration, and customer-specific architectures. Focus on validating multi-node GPU performance, troubleshooting distributed infrastructure, and automating architecture and deployment workflows with AI tooling and Infrastructure-as-Code.
Location: UK
Company
Nscale provides a GPU cloud for AI start-ups and enterprise customers, focused on high-performance, cost-effective infrastructure for AI development and workloads.
What you will do
- Design end-to-end GPU infrastructure solutions covering compute, networking, storage, data-centre systems, orchestration, and management platforms.
- Architect GPU clusters, NVLink/NVSwitch domains, leaf/spine and InfiniBand or Ethernet fabrics, storage systems, and multi-tenant scheduling environments.
- Engage with customers to translate workload requirements into technical architectures, specifications, reference designs, and implementation plans.
- Define validation and acceptance plans, benchmark GPU clusters with NCCL, and troubleshoot multi-node performance, fabric, interconnect, and configuration issues.
- Automate architecture and deployment workflows using AI tooling, Infrastructure-as-Code, scripting, and generated bills of materials and network topologies.
- Establish reliability, observability, health-check, monitoring, and operational-readiness requirements for production GPU infrastructure.
Requirements
- 10+ years of experience in solution architecture, infrastructure engineering, high-performance computing, or large-scale data-centre environments.
- Strong experience designing large-scale GPU infrastructure and AI/HPC solutions across bare-metal compute, networking, orchestration, and workload management.
- Deep knowledge of GPU architectures, NVLink/NVSwitch, PCIe, GPUDirect RDMA, InfiniBand, RoCE, congestion control, and rail-optimised fabrics.
- Production experience with Kubernetes, Slurm, bare-metal provisioning, NCCL benchmarking, GPU diagnostics, and multi-node cluster validation.
- Strong Python or Go scripting and automation skills, with experience using Terraform, Ansible, and modern AI-assisted engineering workflows.
- Experience with AI storage and workload technologies such as Lustre, GPFS, WEKA, BeeGFS, NFS, PyTorch, DeepSpeed, or Megatron-style training stacks.
Nice to have
- Customer-facing experience in Solution Architecture, Pre-Sales Engineering, or Technical Advisory roles.
- Background in hyperscale cloud, GPU infrastructure, HPC, or AI infrastructure environments.
- Experience influencing technical decisions across multiple engineering disciplines in fast-paced and ambiguous environments.
Culture & Benefits
- Collaborative, supportive, and innovative working environment with an emphasis on ownership, accountability, openness, and transparency.
- Competitive package including base salary and equity, with reviews every 12 months.
- Flexible workplace with autonomy to shape the working day.
- Progression plan focused on solving complex technical challenges and influencing GPU cloud architecture.
- Equal-opportunity environment with support for workplace accommodations.
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