Senior Solutions Architect, Physical AI Cloud

NVIDIA
Santa Clara, California
Workplace: HybridFull timeUSD 152,000 - 287,500 annuallyFunction: Solutions Engineering & Sales EngineeringExperience: 5+ yearsEducation: bachelorsSkills: ["Communication","Mentorship","Collaboration","Technical guidance"]

Design and scale Kubernetes-native environments for distributed Physical AI robotics workloads, partnering with product, engineering, and business teams to accelerate enterprise adoption. Build scalable, observable, GPU-accelerated agentic pipelines across NVIDIA frameworks, including data factories for ingestion to synthetic data generation and evaluation. Translate customer requirements into optimized cloud-native architectures and improve scheduling, cost, storage, networking, and GPU utilization while enabling fast distributed inference using NVIDIA inference technologies.

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FursaFursa
NVIDIA
NVIDIA
22 hours ago

Senior Solutions Architect, Physical AI Cloud

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Source: Company careers pageValidated by: Fursa AI
Last checked: 22 hours agoStatus: Live

Job Summary

Design and scale Kubernetes-native environments for distributed Physical AI robotics workloads, partnering with product, engineering, and business teams to accelerate enterprise adoption. Build scalable, observable, GPU-accelerated agentic pipelines across NVIDIA frameworks, including data factories for ingestion to synthetic data generation and evaluation. Translate customer requirements into optimized cloud-native architectures and improve scheduling, cost, storage, networking, and GPU utilization while enabling fast distributed inference using NVIDIA inference technologies.
Location: Santa Clara, California
Workplace: Hybrid
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Help partners build scalable, observable, GPU-accelerated Physical AI pipelines using agentic workflows and NVIDIA frameworks such as OSMO.
  • •Build Physical AI data factories for ingestion, preprocessing, annotation, filtering, synthetic data generation, training, simulation, and evaluation.
  • •Translate customer requirements into optimized cloud-native architectures to improve scheduling, cost, storage access, networking, and GPU utilization across hybrid infrastructure.
  • •Accelerate distributed inference using NVIDIA technologies including NIM, TensorRT-LLM, vLLM, and SGLang.
  • •Provide technical guidance and mentorship to customers implementing Physical AI at scale while collaborating with product, engineering, and business teams.

Pay and Benefits

Salary: USD 152,000 - 287,500 annually

Key Requirements

  • •BS in Computer Science, Computer Engineering, or related field, or equivalent experience.
  • •5+ years in Solution Architecture or Infrastructure Engineering, progressing AI/ML systems from proof of concept to production on private/public cloud.
  • •Experience scaling robotics workloads (e.g., multimodal model training/inference, robot learning and simulation, large-scale data processing and generation).
  • •Hands-on experience designing, deploying, and operating Kubernetes-based platforms for distributed GPU and AI workloads.
  • •Strong expertise in networking, storage, workflow orchestration (e.g., Airflow, Argo), DevOps practices (GitOps, IaC, observability), and orchestration of efficient GPU workloads.
Experience:5+ yearsRoboticsAI/MLCloud-nativeGPU-accelerated
Education:Bachelor's
Skills:CommunicationMentorshipCollaborationTechnical guidance
Tech Stack:KubernetesOSMOAirflowArgoGitOpsIaCObservabilityDNSLBTCP/IPFirewallsNVIDIANIMTensorRT-LLMVLLMSGLangIsaac LabIsaac SimGR00TCosmos

Company Brief

NVIDIA
Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1993
Glassdoor
Glassdoor: 4.3
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