Solutions Engineer

About the role

Nscale is seeking a Principal Presales Engineer to join their commercial team and assist customers in evaluating and adopting AI infrastructure solutions. This role involves partnering with account executives and technical teams to manage the full sales cycle, from discovery and solution design to proof of concept and onboarding. The ideal candidate will translate complex GPU and AI concepts into clear business value for both technical and non-technical stakeholders.

Responsibilities

• Support the commercial team in qualifying customer opportunities and identifying technical requirements early in the sales process
• Deliver compelling product demos, technical presentations, workshops, and architecture sessions for prospective customers and partners
• Translate customer AI, HPC, and infrastructure requirements into clear solution designs using Nscale’s platform
• Develop and present solution proposals that align technical architecture with customer business outcomes
• Work closely with customers to understand workloads, deployment requirements, performance expectations, and scaling plans
• Support proof of concepts, evaluations, onboarding projects, and technical validation activities
• Partner with product, engineering, and operations teams to ensure proposed solutions are realistic, scalable, and aligned with platform standards
• Provide guidance on compute, networking, storage, orchestration, and workload optimisation for AI and machine learning use cases

Required skills

• Presales engineering
• Solutions architecture
• Cloud architecture
• Cloud infrastructure
• GPU compute
• AI/ML workloads
• Kubernetes
• Slurm
• Orchestration platforms
• Networking
• Storage
• Distributed compute

Nice to have

• Terraform
• InfiniBand
• RDMA
• RoCE
• APIs
• Open-weight model training

About the Company

Nscale is a GPU cloud engineered for AI, providing cost-effective, high-performance infrastructure for AI start-ups and large enterprise customers. The company focuses on reducing the complexity of AI development to support strategic business outcomes like cost management and rapid innovation.