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Submer

Immersion cooling systems for data centers

AI Infrastructure Solutions Architect

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours
Full-timeRemote in IndiaNo salary listed

About the Job

Requirements

  • A bachelor's degree in Computer Science, Information Technology, Electronics, Electrical Engineering, or a related discipline is required.
  • A master's degree is preferred.
  • Eight to fifteen years of experience in enterprise infrastructure, high-performance computing, AI infrastructure, or solution architecture is required.
  • At least five years of experience in a customer-facing presales or solutions architecture role is required.
  • Experience designing GPU-based AI infrastructure and high-density compute environments is highly desirable.
  • Preferred certifications include NVIDIA Certified Professional or equivalent, AWS Solutions Architect, Microsoft Azure Solutions Architect, Red Hat OpenShift, VMware VCP, Cisco CCNP/CCIE, Kubernetes CKA/CKAD, and ITIL Foundation.
  • Technical expertise includes AI infrastructure architecture, GPU compute platforms, high-performance computing infrastructure, infrastructure sizing, solution design, AI networking, storage architecture, Kubernetes, and AI platform integration.
  • Business expertise includes technical presales, solution consulting, proposal development, technical bid management, customer engagement, and executive presentations.
  • Collaboration capabilities include cross-functional leadership, stakeholder management, technical mentoring, OEM engagement, and customer relationship management.
  • Technical expertise across compute includes NVIDIA GPU platforms, AMD GPU platforms, Intel AI platforms, GPU cluster design, AI Factory architectures, and high-performance computing infrastructure.
  • Networking expertise includes Ethernet, InfiniBand, RoCE, Spine-Leaf architectures, and AI fabric design.
  • Storage expertise includes parallel file systems, high-performance NAS, object storage, NVMe-over-Fabrics, and AI data pipelines.
  • Software expertise includes Kubernetes, Docker, Slurm, NVIDIA AI Enterprise, GPU scheduling, cluster management, and infrastructure automation.
  • Infrastructure expertise includes server platforms, rack integration, infrastructure sizing, high-density deployments, liquid-cooled server technologies, infrastructure monitoring, and DCIM integration.

Responsibilities

  • Partner with Sales to qualify AI infrastructure opportunities.
  • Engage with customers to understand AI workloads, performance expectations, scalability requirements, and operational objectives.
  • Conduct technical discovery workshops and architecture discussions.
  • Prepare technical proposals, presentations, and solution demonstrations.
  • Support RFI, RFP, and RFQ responses.
  • Serve as the trusted technical advisor throughout the sales lifecycle.
  • Design complete AI infrastructure solutions encompassing GPU compute clusters, AI Factory infrastructure, high-performance computing platforms, high-performance storage, AI networking fabrics, Kubernetes and container platforms, AI software stack integration, cluster management, security architecture, monitoring and observability, automation platforms, and scalability and expansion planning.
  • Develop solution architectures, infrastructure sizing, bills of materials, reference architectures, technical specifications, solution documentation, and deployment architectures.
  • Work with Facilities Presales, Design, and Engineering teams to ensure AI infrastructure solutions are compatible with the proposed data center environment.
  • Provide technical input on rack power density, rack layouts, GPU server deployment, network topology, cable density, space requirements, liquid cooling interfaces, CDU connectivity requirements, infrastructure dependencies, and expansion strategy.
  • Validate that AI infrastructure can be deployed within facility constraints without taking ownership of the facility design.
  • Collaborate with Delivery and Engineering teams to ensure solution feasibility.
  • Support technical design reviews, OEM interoperability validation, deployment planning, installation readiness, factory acceptance planning, site acceptance planning, commissioning, and technical handover to delivery teams.
  • Maintain ownership of the AI infrastructure solution throughout the project lifecycle.
  • Design for serviceability, scalability, high availability, redundancy, cluster management, monitoring, capacity management, firmware lifecycle, upgrade strategy, infrastructure observability, and operational support requirements.
  • Work with Sales, Product Management, Delivery, Professional Services, Facilities Presales, Facilities Design and Engineering, OEM partners, System Integrators, customer infrastructure teams, and AI Engineering teams.
  • Act as the primary technical interface for AI infrastructure-related discussions.

Desired Qualifications

  • Experience designing GPU-based AI infrastructure and high-density compute environments is highly desirable.

About the Company

Submer

Immersion cooling systems for data centers

Submer sells immersion cooling systems for data centers, including SmartPodX, SmartPodXL, and MicroPod, to operators like hyperscalers, telecoms, government agencies, financial institutions, universities and research institutions, and colocation providers. The products work by submerging servers and other components in a specialized liquid coolant to remove heat more efficiently than air cooling, with modular units that support installation, maintenance, and ongoing operation. Submer differentiates itself through a focused portfolio of immersion cooling products, global showrooms and demonstration centers, and services such as installation, maintenance, and training via the Submer Academy and partner networks. The company aims to cut energy use and operating costs in data centers while boosting sustainability to support workloads in cloud computing, AI, high‑performance computing, and edge deployments.

Company size
51-200
Company stage
Debt Financing
Total funding
$131.2M
Headquarters
Rubí, Spain
Founded
2015

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