Senior Solutions Architect, Generative AI Deployment and AIOps

NVIDIA
Santa Clara, New York
Workplace: OnsiteFull timeUSD 184,000 - 287,500Function: Solutions Engineering & Sales EngineeringExperience: 8+ yearsSkills: ["Communication","Collaboration","Presentation","Problem-solving"]

Senior Solutions Architect focused on Generative AI deployment, AI inference, and MLOps, advising customers on high-value NVIDIA solutions, optimizing AI workloads on Kubernetes, and collaborating with engineering, product, and business teams to deliver scalable AI infrastructure using PyTorch, TensorFlow, and NVIDIA GPUs.

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FursaFursa
NVIDIA
NVIDIA
5 months ago

Senior Solutions Architect, Generative AI Deployment and AIOps

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 4 hours agoStatus: Live

Job Summary

Senior Solutions Architect focused on Generative AI deployment, AI inference, and MLOps, advising customers on high-value NVIDIA solutions, optimizing AI workloads on Kubernetes, and collaborating with engineering, product, and business teams to deliver scalable AI infrastructure using PyTorch, TensorFlow, and NVIDIA GPUs.
Location: Santa Clara, New York
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering

Key Responsibilities

  • •Partner with other solution architects, engineering, product and business teams to define high-value solutions
  • •Engage with developers, researchers, and data scientists across technical areas
  • •Collaborate with lighthouse customers and industry partners targeting our computing platform
  • •Help customers adopt NVIDIA technology and MLOps solutions for creative AI deployments
  • •Analyze performance and power efficiency of AI inference workloads on Kubernetes

Pay and Benefits

Salary: USD 184,000 - 287,500

Key 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 with Deep Learning frameworks such as PyTorch and TensorFlow
  • •Strong fundamentals in programming, optimizations, and software design, especially in Python
  • •Proficiency in problem-solving and debugging skills in GPU orchestration and Multi-Instance GPU (MIG) management within Kubernetes environments
  • •Experience with containerization and orchestration technologies, monitoring, and observability solutions for AI deployments
Experience:8+ yearsAIGPUMLOps
Skills:CommunicationCollaborationPresentationProblem-solving
Tech Stack:PythonPyTorchTensorFlowKubernetesDockerNVIDIA NIMDynamoTensorRTTensorRT-LLMGPU

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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