Senior Solutions Architect, Physical AI Cloud

Nvidia

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CA
Salary: $152,000–$241,500 / yr
Posted: 32 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $199k

This role $197k

$140k most similar roles pay here $262k

This role pays more than 50% of similar roles. Most pay $162,000–$235,750 — the shaded band above. At the midpoint, this role pays about $197k versus about $199k for comparable roles.

Based on 239 similar postings.

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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.

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At a glance

TL;DR · Senior Solutions Architect, Physical AI Cloud

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As a Senior Solutions Architect, Physical AI Cloud, you will join a team focused on helping enterprises deploy and accelerate robotics simulation, synthetic data generation, multi-step model training, and inference at scale. You will design and scale Kubernetes-native environments for distributed robotics workloads while building GPU-accelerated pipelines through agentic workflows and NVIDIA frameworks like OSMO. Your daily responsibilities include developing Physical AI data factories for ingestion, preprocessing, and annotation, as well as optimizing cloud-native architectures to improve scheduling, storage access, and networking. You will utilize technologies including NIM, TensorRT-LLM, vLLM, SGLang, Isaac Lab, Isaac Sim, GR00T, and Cosmos. The role requires expertise in Kubernetes, networking protocols like DNS and TCP/IP, workflow orchestration tools such as Airflow or Argo, and modern DevOps practices including GitOps and Infrastructure as Code to solve complex robotics AI challenges.

What does a Solutions Architect earn in California?

Median $235750 from 45 postings across 8 companies.

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Skills

Kubernetes TensorRT-LLM vLLM SGLang Triton Isaac Sim Isaac Lab ROS2 Airflow Argo GitOps IaC REST gRPC S3 NFS Lustre

What you'll do

Design and scale Kubernetes-native environments for distributed robotics workloads.
Build scalable, observable, GPU-accelerated Physical AI pipelines using agentic workflows and cloud-native technologies.
Develop data factories for ingestion, preprocessing, annotation, synthetic data generation, training, and evaluation.
Translate customer requirements into optimized architectures to improve scheduling, cost, storage, networking, and GPU utilization.
Accelerate distributed inference using NVIDIA technologies like NIM, TensorRT-LLM, vLLM, and SGLang.
Provide technical guidance and mentorship to customers implementing Physical AI at scale.
Deploy and operate Kubernetes-based platforms for distributed GPU and AI workloads across hybrid infrastructures.

What we're looking for

BS in Computer Science, Computer Engineering, or a related field, or equivalent experience.
5+ years of experience in Solution Architecture or Infrastructure Engineering for advancing AI/ML systems to production.
Experience scaling robotics workloads including multimodal model training, inference, robot learning, and simulation.
Hands-on experience designing, deploying, and operating Kubernetes-based platforms for distributed GPU and AI workloads.
Expertise in networking, storage technology, workflow orchestration (Airflow, Argo), and modern DevOps practices (GitOps, IaC, Observability).
Excellent communication skills to convey technical concepts to diverse audiences.
Experience with robotics frameworks like ROS2 or NVIDIA simulation and AI platforms such as Isaac Lab, Isaac Sim, GR00T, or Cosmos (preferred).
Experience with large scale data curation, inference technologies (NIM, Triton, vLLM), or agentic workflows (preferred).

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