HPC AI Solution Architect (S2S)
As a Lead Cloud Integrated Infra Engineer on the Silicon2Service team, you will be responsible for:
- Leading architecture for pursuits and active opportunities, including discovery, requirements, constraints, and target-state design
- Creatively defining reference architectures for on-premises, cloud, and hybrid GPU platforms across compute, network, storage, security, software and operations
- Driving architecture trade-offs and decisions across performance, scalability, reliability, locality, total cost of ownership, time-to-value, and risk
- Owning the technical solution strategy in proposals and RFPs, including architecture narrative, assumptions, dependencies, sizing guidance, and delivery approach
- Facilitating client workshops and technical reviews and translating engineering detail into executive-ready communications
- Architecting complex, innovative technology solutions with a focus on business outcomes, cost of quality, and long-term scalability and sustainability.
- Engaging with C-Suite client leadership during sales and delivery, including leading technical pre-sales discussions, shaping proposals, and supporting the closing of new business opportunities
- Supporting go-to-market strategies, including participation in industry events, conferences, and client briefings
- 10+ years of experience in infrastructure architecture or engineering for large-scale platforms including design, implementation, operations, and optimization.
- 4+ years designing or delivering GPU-accelerated platforms for AI, ML, or high-performance computing
- 3+ years Linux system administration in production environments
- 3+ years designing or operating distributed compute clusters for AI/HPC in hybrid cloud setups, including multi-GPU topologies, partitioning, scheduler integration, and scalability for edge-to-cloud workloads.
- 2+ years with high-performance networking or storage for AI/HPC
- 2+ years building containerized platforms using Kubernetes or Red Hat OpenShift, including GPU operators/drivers, CUDA container runtime, and cluster lifecycle automation
- 2+ years automating infrastructure as code(IaC) with tools like Terraform and Ansible
- At least 2 end-to-end deployments of reference architectures in the cloud or on-prem, including variants with security controls, network segmentation, operational runbooks, and validation testing
- Experience in pre-sales or sales engineering, including discovery, solution demonstrations, and proposal/RFP contributions
- Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
- Limited immigration sponsorship may be available.
- 2+ years implementing AI/HPC cluster scheduling (Slurm and Kubernetes), including multi-tenant queues, quotas, and GPU-aware policies
- 2+ years supporting generative AI infrastructure patterns, including multi-node distributed training
- Experience with AI agents and frameworks
- Experience with high-throughput storage for AI/HPC
- Experience executing NVIDIA co-sell motions with OEMS (Dell, HPC, Lenovo), CSPs ( AWS, Azure, Google Cloud), or independent software vendors ( Run:ai, OpenShift, Weights & Biases)
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