Solution Architect - ISV for AI Infra

Overview

• NVIDIA is looking for an enthusiastic and forward-thinking solution architect to help in the enablement of Industry Software Vendors (ISVs).
• These ISVs are developing the Agentic AI stack for multiply workloads which will be used to empower industry customers.
• As part of the Solution Architecture team, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.
• Join the team and see how you can make a lasting impact on the world by applying AI technology to mass market.
• What you'll be doing: Work with ISVs and end customers to understand their system architecture, technical requirements, and business workflows, then guide them toward the best NVIDIA-based solution.
• Architect hybrid and multi-cloud AI solutions, guiding ISVs and customers on deploying GPU-accelerated workloads across major public clouds and private data centers.
• Design and optimize scalable AI infrastructure solutions, providing best-practice guidance on configuring CPU/GPU servers, storage, and networking for high-performance workloads.
• Support technical discovery, proof-of-concept development, infrastructure validation, and production adoption for industry software platforms.
• Provide technical leadership in deploying AI applications across diverse environments, including bare-metal servers, virtualized instances, and cloud-native containerized clusters.
• Collaborate with headquarters engineering, product, and partner teams in English to resolve technical issues, influence roadmap alignment, and ensure strong execution for strategic ISV engagements.
• Analyze infrastructure bottlenecks, cluster behavior, and deployment trade-offs, then recommend practical architectures that improve performance, scalability, and usability for customers.
• What we need to see: MSc/PhD in Computer Science, Electrical Engineering, IT Infrastructure, or related field (or equivalent experience).
• 3+ years in infrastructure/cloud architecture, technical consulting, or customer-facing technical roles.
• Strong domain expertise with understanding of enterprise infrastructure and real-world workflows.
• Knowledge of GPU architecture and its application in accelerating modern workloads.
• Hands-on experience with enterprise IT infrastructure, including CPU/GPU servers, data centers, and HPC environments.
• Experience with major cloud platforms, especially GPU-accelerated instances and AI services.
• Proficiency in cloud-native tech, containerization (Docker/Podman), and orchestration tools (Kubernetes/Slurm).
• Strong communication skills to translate technical concepts for business stakeholders and collaborate across global teams.
• Ways to stand out from the crowd: Experience working with Independent Software Vendors (ISVs), enterprise software platforms, or technical partner ecosystems.
• Deep expertise in AI infrastructure (AI infra) architecture, including large-scale CPU/GPU cluster design, AI job scheduling, and performance tuning for LLM training/inference.
• Relevant cloud architecture certifications or deep expertise in building edge-to-cloud scalable AI infrastructures.
• Strong customer engagement skills with a proven record of helping partners and customers succeed through technical leadership and execution.