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Senior Solutions Architect, Generative AI Deployment and AIOps

NVIDIA· Architect, Solutions
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Hybrid (Santa Clara, CA), Hybrid (Remote (IL)), Hybrid (Remote (NY)), Hybrid (Remote (CA)), Hybrid (Remote (MD)), Hybrid (Remote (MA))$184k - $287.5k + equityfull-timePosted 6mo ago

About the role

Senior Solutions Architect focused on Generative AI deployment and AI operations (AIOps) with NVIDIA’s AI infrastructure. Responsible for advising customers, defining high-value solutions, analyzing performance and power efficiency of AI inference workloads, and collaborating with internal teams on MLOps and NVIDIA technology adoption.

Responsibilities

  • Partnering with other solution architects, engineering, product and business teams to understand strategies and define high-value solutions
  • Dynamically engaging with developers, scientific researchers, and data scientists across technical areas
  • Strategically partnering with lighthouse customers and industry-specific solution partners
  • Working closely with customers to help them adopt and build creative solutions using NVIDIA technology and MLOps solutions
  • Analyzing performance and power efficiency of AI inference workloads on Kubernetes
  • Some travel to conferences and customers may be required (20%)

Qualifications

  • 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
  • Excellent knowledge of the theory and practice of LLM and DL inference
  • Excellent presentation, communication and collaboration skills

Skills

Required:Deep Learning frameworks (PyTorch, TensorFlow)Python programmingGPU orchestration and MIG management in KubernetesContainerization and orchestration technologiesLLM and DL inference theory/practice

Benefits

  • equity
  • benefits (as per company policy)
Last updated Sep 18, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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