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Open nowPosted 93 days ago

AI Infrastructure Solutions Architect

SUBMER6 open roles

Where
India
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Your applicationOpen nowAI Infrastructure Solutions ArchitectSUBMER · India

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The clock on this job

Early applications get read.

13.4% of postings close within 7 days. Measured by our own scanner across the market. SUBMER postings stay open a median of 16 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.6%3 days
  3. 13.4%7 days
  4. 21.6%14 days
  5. 36.2%30 days
  6. 59.0%60 days
This job: posted 93 days ago

SUBMER median: 16 days open

The posting

Location & work modality: India ( Remote)

About Submer

Submer enables organizations scaling AI to overcome the limits of traditional datacenters across power, compute density and efficiency.

We design and deliver scalable, high-density AI datacenter infrastructure built around industry-leading liquid cooling, supporting everything from early AI deployments to full-scale production environments.

What Impact you will have

We are looking for AI Infrastructure Solutions Architect

Department: Solutions Engineering / Presales

Position Summary

The AI Infrastructure Solutions Architect is responsible for designing end-to-end AI infrastructure solutions that enable customers to deploy scalable, high-performance AI and HPC environments. The role combines technical presales, solution architecture, infrastructure sizing, and deployment planning to deliver commercially viable and operationally sound AI infrastructure solutions.

The architect serves as the technical authority for compute, networking, storage, AI software stack, and infrastructure integration while working closely with Sales, Delivery, Product Management, OEM partners, and the Facilities Presales & Design teams to ensure that the AI infrastructure requirements are fully aligned with the data center's power, cooling, space, and physical infrastructure capabilities.

This role owns the AI infrastructure architecture and complements the facility design process.

What you will do

Key Responsibilities

  1. AI Infrastructure Presales
  • 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.
  1. AI Infrastructure Solution Architecture

Design complete AI infrastructure solutions including:

  • GPU compute clusters
  • AI Factory infrastructure
  • HPC platforms
  • High-performance storage
  • AI networking fabrics (Ethernet, InfiniBand, RoCE)
  • Kubernetes and container platforms
  • AI software stack integration
  • Cluster management
  • Security architecture
  • Monitoring and observability
  • Automation platforms
  • Scalability and expansion planning

Develop:

  • Solution architecture
  • Infrastructure sizing
  • Bill of Materials (BoM)
  • Reference architectures
  • Technical specifications
  • Solution documentation
  • Deployment architecture
  1. Infrastructure Integration with Data Center Design

Work closely with Facilities Presales, Design, and Engineering teams to ensure the AI infrastructure solution is fully compatible with the proposed data center environment.

Provide technical inputs related to:

  • Rack power density
  • Rack layouts
  • GPU server deployment
  • Network topology
  • Cable density
  • Space requirements
  • Liquid cooling interfaces
  • CDU connectivity requirements
  • Infrastructure dependencies
  • Expansion strategy

Validate that the AI infrastructure can be successfully deployed within the facility constraints without owning the facility design itself.

  1. Solution Validation & Delivery Readiness

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 support
  • Technical handover to delivery teams

Maintain ownership of the AI infrastructure solution throughout the project lifecycle.

  1. Operational Architecture

Ensure the proposed solution is designed for long-term operational success by considering:

  • Serviceability
  • Scalability
  • High availability
  • Redundancy
  • Cluster management
  • Monitoring
  • Capacity management
  • Firmware lifecycle
  • Upgrade strategy
  • Infrastructure observability
  • Operational support requirements
  1. Cross-Functional Collaboration

Work closely with:

  • Sales
  • Product Management
  • Delivery
  • Professional Services
  • Facilities Presales
  • Facilities Design & Engineering
  • OEM partners
  • System Integrators
  • Customer Infrastructure teams
  • AI Engineering teams

Act as the primary technical interface for all AI infrastructure-related discussions.

Technical Expertise

AI Compute

  • NVIDIA GPU platforms
  • AMD GPU platforms
  • Intel AI platforms
  • GPU cluster design
  • AI Factory architectures
  • HPC infrastructure

Networking

  • Ethernet (100/200/400/800G)
  • InfiniBand
  • RoCE
  • Spine-Leaf architectures
  • AI fabric design

Storage

  • Parallel file systems
  • High-performance NAS
  • Object storage
  • NVMe-over-Fabrics
  • AI data pipelines

Software

  • Kubernetes
  • Docker
  • Slurm
  • NVIDIA AI Enterprise
  • GPU scheduling
  • Cluster management
  • Infrastructure automation

Infrastructure

  • Server platforms
  • Rack integration
  • Infrastructure sizing
  • High-density deployments
  • Liquid-cooled server technologies
  • Infrastructure monitoring
  • DCIM integration

Qualifications

  • Bachelor's degree in Computer Science, Information Technology, Electronics, Electrical Engineering, or a related discipline.
  • Master's degree is preferred.
  • 8–15 years of experience in enterprise infrastructure, HPC, AI infrastructure, or solution architecture.
  • At least 5 years in a customer-facing Presales or Solutions Architecture role.
  • Experience designing GPU-based AI infrastructure and high-density compute environments is highly desirable.

Preferred Certifications

  • NVIDIA Certified Professional (or equivalent)
  • AWS Solutions Architect
  • Microsoft Azure Solutions Architect
  • Red Hat OpenShift
  • VMware VCP
  • Cisco CCNP/CCIE
  • Kubernetes (CKA/CKAD)
  • ITIL Foundation

Core Competencies

Technical

  • AI Infrastructure Architecture
  • GPU Compute Platforms
  • HPC Infrastructure
  • Infrastructure Sizing
  • Solution Design
  • AI Networking
  • Storage Architecture
  • Kubernetes
  • AI Platform Integration

Business

  • Technical Presales
  • Solution Consulting
  • Proposal Development
  • Technical Bid Management
  • Customer Engagement
  • Executive Presentations

Collaboration

  • Cross-functional leadership
  • Stakeholder management
  • Technical mentoring
  • OEM engagement
  • Customer relationship management

What we offer

  • Attractive compensation package reflecting your expertise and experience.
  • A great work environment characterized by friendliness, international diversity, flexibility, and a hybrid-friendly approach.
  • You´ll be part of a fast-growing scale-up with a mission to make a positive impact, offering an exciting career evolution.

Our job titles may span more than one job level. The actual base pay is dependent on a number of factors, such as transferable skills, work experience, business needs and market demands.

Our inclusive responsibility

Submer is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other protected category under applicable law.

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