NVIDIA is seeking outstanding AI Solutions Architects to assist and support customers that are building solutions with our newest AI technology. At NVIDIA, our solutions architects work across different teams and enjoy helping customers with the latest Accelerated Data Analytics and Deep Learning software and hardware platforms. We're looking to grow our company, and build our teams with the smartest people in the world. Would you like to join us at the forefront of technological advancement?
This role will focus on helping ISVs understand, adopt, and commercialize NVIDIA acceleration technologies across structured data processing, analytics, unstructured data, retrieval, and agentic AI workflows. This role is an excellent opportunity to work in an interdisciplinary team at NVIDIA! You will partner closely with ISVs, product, engineering, developer relations, business development, sales, and segment teams to identify high-impact use cases, develop early POCs and build repeatable enablement.
What You Will Be Doing:
Drive technical GTM with Data Platform ISVs across query engines, databases, analytics platforms, data processing frameworks, and AI data infrastructure.
Partner with ISVs on discovery, architecture reviews, technical deep dives, POCs, benchmarks, demos, and customer-facing enablement
Help ISVs identify the right NVIDIA acceleration paths for their platforms and use cases, including cuDF, Spark RAPIDS, Polars, Velox, cuVS, and related NVIDIA libraries
Build repeatable GTM assets such as reference architectures, technical playbooks, demos, blogs, talks, and customer training
Support emerging data platform use cases for GenAI, including unstructured data processing, RAG pipelines, data preparation, and retrieval workflows
Travel up to 20% for conferences and customers may be required
What We Need To See:
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 Machine Learning, Deep Learning and Data Analytics
Strong background in data platforms, distributed systems, analytics, databases, or systems for managing and processing data
Familiarity with data ecosystems such as Spark, Pandas, Polars, DuckDB, Trino, Presto, Velox, vector databases, or unstructured data pipelines
Experience working with ISVs, partners, or enterprise customers in a solutions architecture or field engineering role
Excellent presentation, communication and collaboration skills
Ways To Stand Out From The Crowd:
Hands-on experience with NVIDIA GPUs and software libraries, such as NeMo Retriever, cuVS, RAPIDS and cuDF
Background in RAG, agentic AI, unstructured data processing, or inference and data platform integration
Excellent C/C++ programming skills, including debugging, profiling, code optimization, performance analysis, and test design
Familiarity with parallel programming and distributed computing platforms
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- BS, MS, or PhD in Computer Science, Engineering, Physics, Mathematics, or equivalent experience
- 8+ years hands-on experience with Machine Learning, Deep Learning, and Data Analytics
- Strong background in data platforms, distributed systems, analytics, or databases
- Familiarity with data ecosystems such as Spark, Pandas, Polars, DuckDB, Trino, Presto, Velox, vector databases, or unstructured data pipelines
- Experience working with ISVs, partners, or enterprise customers in a solutions architecture or field engineering role
- Excellent presentation, communication, and collaboration skills
- Hands-on experience with NVIDIA GPUs and libraries (NeMo Retriever, cuVS, RAPIDS, cuDF)
- Background in RAG, agentic AI, unstructured data processing, or inference and data platform integration
- Excellent C/C++ programming skills including debugging, profiling, code optimization, and performance analysis
- Familiarity with parallel programming and distributed computing platforms
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 — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
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.”
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