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
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.
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
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.
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.
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
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 prospect 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.
📌 AI Infrastructure Solutions Architect (India)
🏢 Submer
📍 India