Submer

• Act as a trusted technical advisor to customers, partners, and resellers across India. • Design end-to-end data center architectures (compute, storage, networking) integrated with immersion cooling. • Drive technical proposals, BoQs, consulting documents, and RFP responses. • Deliver presentations, workshops, and training for customers and partners. • Collaborate with Submer Design & Build, sales, and product teams to ensure solution quality and innovation. • Support and influence strategic and transformational AI/HPC data centers in India, aligned with Vision 2030. • Act as the voice of the field, providing feedback to improve Submer’s products and services. • Work with ecosystem alliances — including NVIDIA, Intel, Dell, HP, Supermicro, AMD, and local integrators — to deliver end-to-end AI and HPC solutions. • Be willing to travel across India and work flexibly in hybrid/remote environments.

• Lead Strategic Customer Engagements as a trusted advisor to enterprise customers • Translate complex requirements into tailored solution roadmaps • Drive meaningful conversations with C-level stakeholders • Lead strategic and partner sales initiatives focused on large-scale enterprise projects • Identify and cultivate partnerships that align with Submer’s value proposition • Monitor industry trends and regulatory developments to anticipate market shifts • Partner closely with internal teams to co-develop proposals that deliver measurable business value • Establish and nurture enduring relationships with customers and strategic partners • Represent Submer at key industry events to strengthen brand presence in the India region

• Become a Subject Matter Expert (SME) in IT infrastructure and integration for technically complex projects and tenders. • Work closely with the Middle East Sales Team, building a trusted technical relationship with customers. • Actively engage with the Sales teams to support them in their deals and proposals. • Follow a standard procedure to validate and qualify opportunities from a technical IT perspective. • Drive the technical relationship with customers, ensuring alignment between their IT requirements and Submer’s technology roadmap. • Create and develop technical IT proposals detailing server, networking, and communication system integrations. • Review, validate, and provide preliminary IT architecture designs, ensuring proper integration between Submer’s solutions and the customer’s IT ecosystem during the sales process.

• Build and operate the engineering automation platform that enables repeatable, secure, and scalable deployment of the GPU cloud platform across environments. • Design and maintain the tooling, pipelines, and infrastructure-as-code foundations used to deploy vendor components, platform services, and supporting environments consistently and at scale. • Work across Kubernetes, Terraform, Kustomize, GitHub Actions, secrets management, storage, and observability, ensuring deployments are reproducible, secure, and maintainable. • Independently deliver major automation and deployment capabilities, improving operational quality, and helping teams adopt reliable deployment patterns.

• Build and maintain complex financial models for data center and cloud infrastructure investments, including greenfield developments and acquisitions • Support capital allocation decisions through detailed investment analysis (NPV, IRR, sensitivities, scenario modeling) • Partner with commercial, operations, and strategy teams to evaluate new business opportunities in AI, cloud, and hyperscale data center markets • Develop long-term forecasts, budgets, and performance dashboards for infrastructure assets • Conduct market analysis and benchmarking across digital infrastructure and energy sectors • Assist in fundraising, debt structuring, and refinancing processes, including lender presentations and data room preparation • Monitor asset performance versus plan, identify risks and opportunities, and provide actionable insights to senior management • Prepare materials for internal stakeholders, investors, and board reporting.

• Design, build, and operate the compute orchestration layer powering a GPU-native cloud platform for AI and high-performance workloads. • Maintain the existing CloudStack code base used in current production deployments. • Integrate new upstream CloudStack releases into the internal platform fork. • Perform upgrades of existing customer environments to newer CloudStack versions. • Design and execute safe upgrade paths for running production environments. • Troubleshoot orchestration and provisioning issues in existing deployments. • Maintain and troubleshoot CloudStack VPC networking. • Work with and understand CloudStack Debian VPC routers. • Manage networking implementations based on Open vSwitch (OVS) and OVN. • Improve the reliability of network orchestration components. • Manage hypervisor implementations based on KVM and QEMU. • Maintain and evolve the code responsible for QEMU GPU passthrough, including PCI mapping and exposure of L40S, RTX 6000 Pro, and H200 GPUs to virtual machines. • Design orchestration and scheduling primitives for the next-generation platform based on Kubernetes, Slurm, and Argo Workflows. • Build orchestration workflows that expose GPU and CPU compute resources to platform users. • Implement Kubernetes scheduling strategies including GPU partitioning, Multi-GPU job placement, and Topology-aware scheduling for distributed training and inference. • Design and implement Kubernetes-based GPU/CPU scheduling infrastructure for multi-tenant AI workloads. • Design and operate Slurm-based HPC scheduling environments integrated with Kubernetes clusters. • Implement support for Multi-node distributed GPU training, Gang scheduling, and build automation for Dynamic Slurm node registration. • Design and implement workflow orchestration using Argo Workflows and develop reusable workflow templates for common platform workloads.

• Partner with the sales team during the pre-sales cycle to understand customer requirements and translate them into technical solutions for GPUaaS, Cloud Gaming, AI workloads and edge compute deployments. • Design and validate solution architectures including GPU infrastructure, networking, storage, orchestration, and platform integration within telecom operator environments. • Evaluate customer infrastructure, technical constraints, and deployment scenarios to determine feasibility and ensure alignment with Radian Arc’s platform capabilities. • Develop and validate detailed BOMs for infrastructure deployments including GPU servers, networking, storage, and supporting components. • Work with sales and finance teams to prepare technical proposals, solution documentation, pricing inputs, and quotes for customer opportunities. • Participate in customer meetings, technical workshops, and discovery sessions to present Radian Arc’s platform capabilities and answer technical questions. • Collaborate with technology partners and hardware vendors to ensure accurate configurations, pricing, and solution compatibility. • Assist in preparing technical documentation required for proposals, contracts, and order processing including system diagrams, architecture overviews, and deployment requirements. • Work closely with Product, Engineering, and Service Delivery teams to ensure proposed solutions align with operational capabilities and deployment timelines. • Help refine internal tools, templates, and processes for solution design, quoting, and sales engineering workflows.

• Design, implement, and maintain backend platform services in Go. • Build and evolve control plane APIs for platform and product capabilities. • Develop durable provisioning and lifecycle workflows using orchestration patterns. • Build and maintain frontend and control plane UI components using TypeScript/JavaScript. • Use AI-assisted development tools to accelerate frontend implementation, iteration, and refactoring. • Integrate infrastructure systems such as CloudStack, Kubernetes, container runtimes, and image management into product APIs. • Connect platform services with identity, usage metering, billing, and audit systems. • Model platform state and service interactions across distributed components. • Build robust integrations with systems such as Temporal, Keycloak, OpenMeter, MongoDB, PostgreSQL, RabbitMQ, Kafka, Redis, and ClickHouse. • Ensure backend services are secure, observable, testable, and operationally reliable. • Collaborate closely with DevOps, and infrastructure engineers to deliver end-to-end platform features. • Contribute to engineering standards, service design patterns, and API quality across the platform.

• Build and operate the engineering automation platform that enables repeatable, secure, and scalable deployment of the GPU cloud platform across environments. • Design and maintain the tooling, pipelines, and infrastructure-as-code foundations used to deploy vendor components, platform services, and supporting environments consistently and at scale. • Ensure that deployments are reproducible, secure, and maintainable. • Design, build, and maintain CI/CD pipelines for platform components and supporting services. • Manage infrastructure automation using Terraform and related IaC tooling. • Implement GitOps-style deployment workflows for Kubernetes-based platform services. • Standardize and automate environment provisioning across development, staging, and production. • Maintain developer environments and improve engineering productivity through better tooling and automation. • Automate deployment of vendor and platform components such as Kubernetes, databases, storage, observability, identity, and messaging systems. • Manage secrets and configuration workflows using centralized secret management practices.