This role pays more than
83%
of similar roles. Most pay
$160,982–$235,750
— the shaded band above.
At the midpoint, this role pays about
$236k
versus about
$198k
for comparable roles.
Based on 239 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
896 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 876 roles with salary data.
Senior Solutions Architect, AI Infrastructure Enterprise ISVs joins an interdisciplinary team to support customers building solutions with advanced AI and accelerated computing technologies. This role focuses on helping ISVs adopt accelerated infrastructure for training, fine-tuning, inference, retrieval, and agentic AI workloads. You will serve as a technical advisor for GPU and networking systems, cluster design, orchestration, validation, and production deployment for AI data centers. Responsibilities include conducting architecture reviews, proofs of concept, and building reference architectures, deployment guides, and whitepapers. Key technical requirements include expertise in distributed systems, high-performance computing, and cloud infrastructure. You will work with technologies such as InfiniBand, Ethernet, RDMA, OpenMPI, and NCCL while managing workloads involving RAG and LLM training. The role addresses the complex challenge of optimizing large-scale clusters for reliable performance across compute, storage, and networking layers.
What does a Solutions Architect earn in Remote?
Median $231100 from 71 postings across 13 companies.
Support customers in deploying workloads for training, fine-tuning, inference, retrieval, and agentic AI.
Provide technical advisory on GPU and networking systems, including InfiniBand and RDMA technologies.
What we're looking for
BS, MS, or PhD in Computer Science, Engineering, Physics, Mathematics, or a related field (or equivalent experience).
8+ years of hands-on experience in AI infrastructure, accelerated computing, distributed systems, cloud infrastructure, HPC, or machine learning platforms.
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 including InfiniBand, Ethernet, RDMA, and network performance tuning.
Familiarity with infrastructure requirements for AI workloads like distributed training, inference serving, and storage performance.
Strong communication, presentation, problem-solving, documentation, and collaboration skills.
Experience with LLM workflows, GPU communication patterns (NCCL, OpenMPI), and benchmarking tools like MLPerf.
Remote (Santa Clara, CA)+143 days ago
$184,000–$287,500
GPU
InfiniBand
RoCE
RDMA
NCCL
NVLink
NVSwitch
Kubernetes
Slurm
Python
Linux
High-Performance Computing
Distributed Systems
Shell Scripting
DCGM
Nsight Systems