Solutions Architect - Cloud Infrastructure

We are excited to announce an opening for a Cloud Solution Architect at NVIDIA and are seeking a passionate individual with a strong interest in large-scale GPU infrastructure and AI Factory deployments! If you are enthusiastic about contributing to projects that push the boundaries of cloud-based AI and resilience in large-scale environments, we invite you to read on. NVIDIA is renowned as one of the most sought-after employers in the technology world, offering highly competitive benefits. We are home to some of the most innovative and forward-thinking individuals globally. If you are creative, autonomous, and eager to apply your skills and knowledge in a dynamic environment, we want to hear from you!

What you'll be doing:

• Working as a key member of our cloud solutions team, you will be the go-to technical expert on NVIDIA AI Factory solutions and large-scale GPU infrastructure, helping clients architect and deploy resilient, telemetry-driven AI compute environments at unprecedented scale.

• Collaborating directly with engineering teams to secure design wins, address challenges, and deploy solutions into production, with a focus on developing robust tooling for observability, failure recovery, and infrastructure-level performance optimization.

• Acting as a trusted advisor to our clients, understanding their cloud environment, translating requirements into technical solutions, and providing guidance on optimizing NVIDIA AI Factories for scalable, reliable, and high-performance workloads.

What we need to see:

• 2+ years of experience in large-scale cloud infrastructure engineering, distributed AI/ML systems, or GPU cluster deployment and management.

• A BS in Computer Science, Electrical Engineering, Mathematics, or Physics, or equivalent experience.

• Proven understanding of large-scale computing systems architecture, including multi-node GPU clusters, high-performance networking, and distributed storage.

• Experience with infrastructure-as-code, automation, and configuration management for large-scale deployments.

• A passion for machine learning and AI, and the drive to continually learn and apply new technologies.

• Excellent interpersonal skills, including the ability to explain complex technical topics to non-experts.

Ways to stand out from the crowd:

• Expertise with orchestration and workload management tools like Slurm, Kubernetes, Run:ai, or similar platforms for GPU resource scheduling.

• Knowledge of AI training and inference performance optimization at scale, including distributed training frameworks and multi-node communication patterns.

• Hands-on experience designing telemetry systems and failure recovery mechanisms for large-scale cloud infrastructures including observability tools such as Grafana, Prometheus, and OpenTelemetry.

• Proficiency in deploying and managing cloud-native solutions using platforms such as AWS, Azure, or Google Cloud, with a focus on GPU-accelerated workloads.

• Deep expertise with high-performance networking technologies, particularly NVIDIA InfiniBand, NCCL, and GPU-Direct RDMA for large-scale AI workloads.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 120,000 USD - 189,750 USD for Level 2, and 148,000 USD - 235,750 USD for Level 3.Applications for this job will be accepted at least until October 11, 2025.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.