Solutions Architect, AI Factory Infrastructure
NVIDIA · North Carolina, United States
- Hybrid
- Full-time
- $124,000 / year
- North Carolina, United States
Job highlights
- Design AI data center solutions for customers.
- Optimize AI workloads and infrastructure performance.
- Focus on hybrid cloud and on-prem deployments.
- Requires a degree and 3+ years experience.
- Work with cutting-edge AI technologies.
About the role
Solutions Architect AI Factory Infrastructure - NVIDIA AI Infrastructure Team
Are you passionate about enabling the next generation of AI development? We are looking for an early-in-career Solution Architect to join the growing NVIDIA AI Infrastructure team. NVIDIA is the world leader in computer graphics, artificial intelligence, and accelerated computing. We're in search of creative minds like you to help customers design, architect and implement accelerated computing data center solutions that will power workflows including AI inference at scale and physical AI through digital simulation.
NVIDIA solutions are built around industry leading AI software tools, but these tools are only as good as the infrastructure that enable the workloads. On this team, you will do full stack design including hardware architecture, workload orchestration and application performance tuning. At NVIDIA, you will be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
What You'll Be Doing
- Help customers with their AI factory journey, including workflow pipelines and performance optimization.
- Focus data center implementations for inference use cases, including distributed, disaggregated and scaled out workflows.
- Scope physical AI journeys on Omniverse, including synthetic data generation, data aggregation, application development and simulation pipelines.
- Lead technical sales activities for AI factories with focus on hybrid deployments between cloud and on-prem.
- Deliver hybrid cloud architectures for data pipelines, storage, security and user streaming connectivity.
- Providing expertise in infrastructure workflows, including hardware, task coordination and application tuning.
- Understand different solutions trade-offs and propose enterprise customers the best architecture and technical execution.
- Work directly with key customers to understand workflows and share feedback with internal product and engineering teams.
What We Need To See
- Bachelor's degree or equivalent experience in Engineering or Computer Science.
- 3+ years of meaningful work experience, ideally in an IT infrastructure or related field of expertise.
- An outstanding passion for groundbreaking IT infrastructures that optimize AI workloads.
- Knowledge of infrastructure management including Linux, Kubernetes, Ethernet networking, cloud native tooling.
- Familiarity with Linux system environments including using Linux for systems administration.
- Comfortable with Python programming.
- Understanding how software and hardware work together to optimize applications.
- Ability to work independently with a remote team with minimal direction.
- Outstanding communication skills, strong interpersonal and be an excellent teammate!
Ways To Stand Out From The Crowd
- Experience with on-prem infrastructure architecture and big cloud deployments.
- Experience with cloud native tooling including Terraform, Kubernetes, Helm.
- Background in building large scale infrastructure that deliver workloads via containers.
- Experience developing and deploying solutions in hybrid and/or cloud environments.
- Critical thinking capabilities that leverage fundamentals to deduce solutions to unforeseen problems.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 25, 2026.
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.
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- AI Infrastructure
- Solutions Architecture
- Data Center Solutions
- Cloud Architecture
- Kubernetes
- Linux
- Python
- Hybrid Cloud
- Workload Orchestration
- Performance Tuning
Skills & topics
- Solutions Architect
- AI Infrastructure
- Data Center Solutions
- Cloud Architecture
- Kubernetes
- Linux
- Python
- Hybrid Cloud
- Workload Orchestration
- Performance Tuning
- Engineering
- Computer Science
- IT Infrastructure
- System Administration
- Software Development
- Hardware Architecture
- Technical Sales
- NVIDIA
- Early Career
- Entry Level
How to get hired
- Tailor your resume: Highlight experience with AI infrastructure, Linux, Kubernetes, and Python. Emphasize hybrid and cloud deployment skills.
- Craft a compelling cover letter: Showcase your passion for AI infrastructure and your ability to optimize AI workloads.
- Prepare for technical interviews: Be ready to discuss data center solutions, cloud architectures, and infrastructure management.
- Demonstrate teamwork: Highlight your communication and interpersonal skills, crucial for collaborating with a remote team.
Technical preparation
Behavioral questions
Frequently asked questions
- What is the typical career progression for a Solutions Architect, AI Factory Infrastructure at NVIDIA?
- NVIDIA offers clear career paths. As a Solutions Architect, AI Factory Infrastructure, you can advance from Level 2 to Level 3 and potentially into lead or management roles within the AI Infrastructure team. Your growth will be supported by continuous learning and exposure to cutting-edge projects.
- Does NVIDIA offer remote work options for Solutions Architect roles?
- This role requires the ability to work independently with a remote team. While specific work arrangements can vary, NVIDIA is known for its flexibility and supportive remote work culture, allowing collaboration across different locations.
- What are the key technologies emphasized in the Solutions Architect, AI Factory Infrastructure role at NVIDIA?
- Key technologies include AI infrastructure, data center solutions, Kubernetes, Linux, Python, and hybrid cloud architectures. Experience with cloud-native tooling like Terraform and Helm is also highly valued.
- How does NVIDIA handle salary negotiations for Solutions Architect positions?
- NVIDIA determines base salary based on your location, experience, and the pay of employees in similar positions. The provided ranges for Level 2 and Level 3 indicate NVIDIA's competitive compensation structure. Equity and benefits are also part of the total compensation package.
- What is the application deadline for the Solutions Architect, AI Factory Infrastructure position?
- Applications for this job will be accepted at least until April 25, 2026. It is advisable to apply well before this date to ensure your application is considered.
- Can I apply for similar Solutions Architect roles at NVIDIA if this one isn't a perfect fit?
- Yes, NVIDIA is a large technology leader. If this specific Solutions Architect, AI Factory Infrastructure role isn't an exact match, we encourage you to explore other open positions at NVIDIA that align with your skills and career aspirations.
- What is the importance of Python programming for this Solutions Architect role?
- Python programming is a required skill for this Solutions Architect role. It's crucial for understanding how software and hardware work together to optimize applications and for various scripting and automation tasks within the AI infrastructure.