NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Want to be part of the team that empowers NVIDIA's OEM technical counterparts to develop accelerated compute and AI solutions for their customers? We are looking for a hardworking and self-starting Solutions Architect with a passion for accelerated compute, data workflows and AI security to join our Solutions Architecture and Engineering team. This role focuses on scaling the efficiency of our information and protection integrations, ensuring our customers and partners are equipped to build the future of innovative defense.
As a Solutions Architect in Accelerated Compute Data & Security passionate about high-performance computing, you will focus on integrating NVIDIA’s software and tools with our OEM partners’ offerings. This may involve working with AI Data Pipeline solutions. Your efforts will center on driving adoption, building proof-of-concept technologies, and aligning our technical messaging with our OEMs' broader product strategies.
What you'll be doing:
Design and implement GPU-accelerated pipelines capable of processing very large (multi-TB and PB sizes) cyber, network, and industry datasets.
Develop proof-of-concept discussions that assist and illustrate how to address accelerated and AI compute workloads to tackle real customer issues.
Function as a technical lead and liaison between NVIDIA engineering, product teams, and OEM partners to drive innovative technical and business strategies.
Guide the development of Agentic AI workflows, including semantic search, retrieval-augmented generation (RAG), and Graph Neural Network (GNN) based applications for threat detection.
What we need to see:
BS, MS, or PhD in Computer Science, AI Engineering, Data Science, or a related field (or equivalent experience).
5+ years of experience in roles focused on technology, including Solutions Architecture, Data Science, or AI Research.
Deep expertise in supervised and unsupervised machine learning, deep learning, and statistics, specifically applied to loosely-structured data and security logs.
Strong coding, debugging, and pipeline development skills using Python, C/C++, Bash, and Linux utilities.
Hands-on experience with big data and AI frameworks, including GPU acceleration, Spark, and distributed computing environments.
Exceptional communication and presentation skills, with an ability to distill complex technical topics into clear, understandable content for an engaged audience.
Strong analytical and problem-solving skills, along with an ability to multitask efficiently in a dynamic environment.
Ways to stand out from the crowd:
Direct experience building, deploying, or contributing to NVIDIA opensource projects and tools like Morpheus, RAPIDS, NVIDIA DPU DOCA or similar NVIDIA accelerated compute libraries.
Demonstrated expertise integrating AI workloads with Splunk or data pipeline architectures or AI security protection ecosystems.
Experience working in a technical leadership role or principal investigator capacity on large-scale or secure enterprise projects.
Background in Agentic AI, LLM deployment, and building ingestion/retrieval technologies.
Public speaking experience at industry conferences or large technical events.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.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 a diverse 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, AI Engineering, Data Science, or related field or equivalent experience
- 5+ years of experience in Solutions Architecture, Data Science, or AI Research
- Deep expertise in machine learning, deep learning, and statistics
- Strong coding, debugging, and pipeline development skills
- Hands-on experience with big data and AI frameworks
- Exceptional communication and presentation skills
- Strong analytical and problem-solving skills
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.”
