NVIDIA is the world leader in computer graphics, artificial intelligence, and accelerated computing. For over 30 years, we have been at the forefront of research and engineering around the greatest advances in technology. Our history of innovation drives us to solve the world's hardest problems. Across industries, NVIDIA works with software partners and enterprise customers to accelerate applications, modernize workflows, and unlock new capabilities through AI and accelerated computing.
NVIDIA is looking for a hardworking and forward-thinking solution architect to help in the enablement of Industry Software Vendors (ISVs). These ISVs are developing the Agentic AI stack for multiple workloads which will be used to empower industry customers. As part of the Solution Architecture team, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Join the team and see how you can make a lasting impact on the world by applying AI technology to mass market.
What you'll be doing:
Work with ISVs and end customers to understand their software architecture, technical requirements, and business workflows, then guide them toward the best NVIDIA-based solution.
Help ISVs integrate the right NVIDIA SDKs, libraries, and platform capabilities into their existing applications to accelerate performance, enrich functionality, and improve customer outcomes.
Support technical discovery, proof-of-concept development, solution validation, and production adoption for industry software platforms.
Collaborate with headquarters engineering, product, and partner teams in English to resolve technical issues, influence roadmap alignment, and ensure strong execution for strategic ISV engagements.
Analyze workflow bottlenecks, application behavior, and deployment trade-offs, then recommend practical architectures that improve performance, scalability, and usability for customers.
What we need to see:
MS, PhD in Computer Science, Electrical Engineering, Software Engineer, or related fields (or equivalent experience).
5+ years of relevant work experience in solution architecture, technical consulting, developer relations, platform engineering, or a related customer-facing technical role.
Strong industry background with domain expertise and an understanding of real-world enterprise workflows in one or more verticals.
Working knowledge of GPU architecture fundamentals and how GPU computing can accelerate software applications and industry workloads.
Experience supporting customers or software partners through integration, optimization, deployment, and adoption of technical solutions.
Good understanding of Agentic AI concepts, application patterns, and enabling technologies, with practical familiarity in areas such as CUDA, accelerated AI pipelines, model integration, or AI-based workflow orchestration.
Ability to communicate with both technical and business customers, translate sophisticated requirements into actionable solutions, and work effectively across multi-functional teams.
Strong written and oral communication skills in English, with the ability to collaborate effectively with global management, engineering, and partner teams.
Ways to stand out from the crowd:
Experience working with Independent Software Vendors (ISVs), AI infrastructure, enterprise software platforms, or technical partner ecosystems.
Practical experience with Agentic AI, inference optimization, or NVIDIA AI / accelerated computing libraries.
Strong customer engagement skills with a proven record of helping partners and customers succeed through technical leadership and execution.
Skills Required
- Master’s or PhD in Computer Science, Electrical Engineering, Software Engineering, or a related field, or equivalent experience
- 5+ years of relevant experience in solution architecture, technical consulting, developer relations, platform engineering, or a related customer-facing technical role
- Industry expertise and understanding of real-world enterprise workflows in one or more verticals
- Working knowledge of GPU architecture fundamentals and GPU-accelerated software applications
- Experience supporting customers or software partners through technical integration, optimization, deployment, and adoption
- Understanding of Agentic AI concepts, application patterns, and enabling technologies
- Practical familiarity with CUDA, accelerated AI pipelines, model integration, or AI-based workflow orchestration
- Ability to communicate with technical and business customers and translate requirements into actionable solutions
- Strong written and oral English communication skills
- Experience working with ISVs, AI infrastructure, enterprise software platforms, or technical partner ecosystems
- Practical experience with Agentic AI, inference optimization, or NVIDIA AI and accelerated computing libraries
- Proven customer engagement skills and technical leadership experience
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Company stock and RSUs have driven exceptional total compensation, with a generous employee stock purchase plan and ongoing equity refreshers playing a central role. Feedback suggests historic share-price gains created significant financial upside for many.
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Healthcare Strength — Multiple plan options (HSA, PPO, and in some locations Kaiser) with in-network preventive care covered at 100% and company HSA contributions indicate a robust offering. Mental-health sessions and broad dental, vision, and disability coverage further strengthen the package.
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Parental & Family Support — Up to 22 weeks of fully paid parental leave, adoption and surrogacy reimbursement, and coverage for IVF and egg freezing are highlighted as standout features. Additional family-care resources and caregiving support broaden the appeal.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
