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NVIDIA

Senior Solutions Architect – NVIDIA Cloud Partners

NVIDIA

. Collaborate with NVIDIA Cloud Partners to create, implement, and deliver NVIDIA hardware and software solutions .

Posted 11/3/2026full-timeRemote • United StatesSenior💰 $184,000 - $356,500 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Solution Engineering with a strong focus on NVIDIA hardware and software solutions, including hands-on experience with Cloud architectures and AI model deployment. Proficient in technical presentations and customer engagement throughout the project lifecycle.

Highest-signal resume keywords
Solution Engineering ExperienceNVIDIA GPU ExpertiseCloud Architecture DesignPython ProgrammingDeep Learning Frameworks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Solution EngineeringCloud EngineeringDistributed Cloud ArchitecturesLarge-Scale Cluster EnvironmentsAI Model TrainingMLOpsPerformance TestingFine-TuningSoftware DesignIntegrating Software Application Stacks
Soft Skills
Excellent CommunicationCollaboration SkillsTime ManagementSelf-StarterCustomer-Facing Skills
Tools & Technologies
AWSAzureGCPKubernetesSLURMNVIDIA Software LibrariesNCCLDCGMUFMBase Command Manager
Industry Keywords
GPU Cloud InfrastructureAI BenchmarkingCloud ArchitectureTechnical PresentationsProofs of Concept

Tech Stack

Tools & technologies
AWSAzureCloudGoogle Cloud PlatformKubernetesPythonPyTorchTensorflow

About the role

Key responsibilities & impact
  • Collaborate with NVIDIA Cloud Partners to create, implement, and deliver NVIDIA hardware and software solutions
  • Partner with Solutions Architects, Account Managers, Engineering, Product, and business leaders to align strategies, assess technical needs, and secure business opportunities
  • Serve as the primary technical driver for customers during the design, development, construction, integration, and production of GPU Cloud infrastructure and applications throughout the customer lifecycle
  • Conduct regular technical customer meetings covering project and product details, feature discussions, new technologies, and debugging
  • Build and adopt NVIDIA solutions, including proofs of concept, addressing critical infrastructure, library, and application needs
  • Prepare and deliver technical presentations, workshops, reference architectures, tutorials, and publications to customers

Requirements

What you’ll need
  • BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, Mathematics, or other Engineering fields or equivalent experience
  • 6+ years of Solution Engineering or similar Sales Engineering, Cloud Engineering, or Solution Architecture experience, including direct work with partners and customers
  • Experience crafting and deploying large-scale cluster environments
  • Hands-on experience designing, developing, and delivering distributed Cloud architectures
  • Strong fundamentals in programming, optimizations, and software design
  • Strong experience with Python and deep learning frameworks such as PyTorch and TensorFlow
  • Practical expertise fine-tuning and deploying models
  • Experience integrating software application stacks, libraries, and frameworks to drive consumption from GPU platforms
  • Ability to own and drive complex multidisciplinary technical engagements throughout the full customer lifecycle
  • Efficient time management and ability to balance multiple tasks
  • Excellent presentation, communication, and collaboration skills
  • Self-starter with passion for growth, continuous learning, and sharing insights
  • Practical experience with NVIDIA GPUs, software libraries, frameworks, and foundation models
  • Hands-on expertise with scaled AI cloud environments such as AWS, Azure, and GCP, and on-premises/hybrid infrastructure
  • Familiarity with NVIDIA hardware, networking, storage, and systems technologies such as NCCL, DCGM, UFM, Mission Control, and Base Command Manager
  • Proficiency with large-scale AI model training and deployment, GPU systems, performance testing, AI benchmarking, fine-tuning, MLOps, and cluster orchestration
  • Experience with SLURM, Kubernetes, orchestrators, load balancing, and cloud architecture
  • Experience working with enterprise developers and strong customer-facing skills

Benefits

Comp & perks
  • Equity
  • Benefits
  • Up to 40% travel may be required