Senior Solutions Architect, AI Infrastructure Enterprise ISVs

About the role

NVIDIA is seeking outstanding AI Solutions Architects to assist and support customers that are building solutions with our newest AI and accelerated computing technologies.

Responsibilities

• Partner with ISVs on discovery, architecture reviews, technical deep dives, POCs, benchmarks, demos, and production deployment guidance
• Advises on the design, build-out, and optimization of accelerated AI infrastructure, including large-scale clusters
• Supports infrastructure design across compute, networking, storage, containers, observability, security, power, and data center operations
• Drives adoption of systems monitoring, telemetry, and management tools to improve cluster utilization, reliability, performance and workload insight
• Builds repeatable reference architectures, deployment guides, sizing guidance, benchmark reports, technical playbooks, demos and whitepapers
• Travel up to 20% customer meetings may be required

Requirements

• BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience)
• 8+ years of hands-on experience in AI infrastructure, accelerated computing, distributed systems, cloud infrastructure, high-performance computing, or machine learning platforms
• In-depth knowledge of AI cluster orchestration, scheduling, automation and CI/CD deployment pipelines
• Understanding of data center networking technologies such as InfiniBand, Ethernet, RDMA, network configuration or performance tuning
• Familiarity with infrastructure requirements for AI workloads, including distributed training, inference serving, model deployment, storage performance, and cluster reliability
• Excellent presentation, communication, problem-solving, documentation, and collaboration skills

Qualifications

• Experience architecting AI factories, large GPU clusters, multi-node training environments, production inference platforms
• Experience deploying LLM training, fine-tuning, RAG, and inference workflows on large-scale AI infrastructure
• Experience evaluating cluster performance using benchmarks such as MLPerf, HPL, or workload-specific performance tests
• Applications and systems-level knowledge of OpenMPI, NCCL, distributed training frameworks, and GPU communication patterns
• Experience delivering technical training, workshops, whitepapers, blogs, or mentoring engineers, researchers, and customers on AI/HPC infrastructure

Skills

• Strong experience designing, deploying, and operating accelerated computing infrastructure at scale
• In-depth knowledge of AI cluster orchestration, scheduling, automation and CI/CD deployment pipelines
• Understanding of data center networking technologies such as InfiniBand, Ethernet, RDMA, network configuration or performance tuning
• Familiarity with infrastructure requirements for AI workloads, including distributed training, inference serving, model deployment, storage performance, and cluster reliability
• Excellent presentation, communication, problem-solving, documentation, and collaboration skills

Benefits

• Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
• The base salary range is 184,000 USD - 287,500 USD.
• You will also be eligible for equity and benefits.

Pay

• Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
• The base salary range is 184,000 USD - 287,500 USD.

Schedule

• Full-time