Senior Solutions Architect, Generative AI Deployment and AIOps

NVIDIA
United States
Workplace: OnsiteFull timeUSD 184,000 - 287,500 annuallyFunction: Solutions Engineering & Sales EngineeringExperience: 8+ yearsEducation: bachelorsSkills: ["Presentation","Communication","Collaboration","Problem-solving","Debugging"]

Serve as a trusted AI solutions advisor, partnering with developers, researchers, and internal engineering/product teams to define and deliver high-value Generative AI and LLM proof-of-concepts. Help customers adopt and build solutions on NVIDIA Accelerated Computing platforms and MLOps. Analyze inference performance and power efficiency on Kubernetes, including GPU orchestration and MIG. Collaborate with lighthouse customers and support creative AI workloads end to end.

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FursaFursa
NVIDIA
NVIDIA
1 week ago

Senior Solutions Architect, Generative AI Deployment and AIOps

âś“ Verified Job

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 14 hours agoStatus: Live

Job Summary

Serve as a trusted AI solutions advisor, partnering with developers, researchers, and internal engineering/product teams to define and deliver high-value Generative AI and LLM proof-of-concepts. Help customers adopt and build solutions on NVIDIA Accelerated Computing platforms and MLOps. Analyze inference performance and power efficiency on Kubernetes, including GPU orchestration and MIG. Collaborate with lighthouse customers and support creative AI workloads end to end.
Location: United States
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Partner with other solution architects, engineering, product, and business teams to define high-value AI solutions.
  • •Engage with developers, scientific researchers, and data scientists across technical areas.
  • •Work with customers and industry partners to target NVIDIA’s computing platform for Generative AI deployment.
  • •Support customers in adopting and building creative solutions using NVIDIA technology and MLOps.
  • •Analyze inference workload performance and power efficiency on Kubernetes, including GPU orchestration.
Travel: Medium travel

Pay and Benefits

Salary: USD 184,000 - 287,500 annually
Equity and Bonus:Equity

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 for GPU orchestration and Multi-Instance GPU (MIG) management within Kubernetes environments.
  • •Excellent knowledge of the theory and practice of LLM and DL inference.
Experience:8+ yearsDeep learningLLMsGPUAI inferenceMLOps
Education:Bachelor's in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields
Skills:PresentationCommunicationCollaborationProblem-solvingDebugging
Tech Stack:PyTorchTensorFlowPythonKubernetesGPU orchestrationMulti-Instance GPU (MIG)LLM inferenceMLOpsContainerizationOrchestrationNVIDIA NIMDynamoTensorRTTensorRT-LLMCC++Observability

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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