Solutions Architect – Cloud Providers and Hyperscale
| Company | NVIDIA |
|---|---|
| Location | Seattle, WA, USA, Santa Clara, CA, USA |
| Salary | $148000 – $287500 |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s, PhD |
| Experience Level | Senior |
Requirements
- BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.
- Motivation and skills to help drive technical pre-sales activities.
- 5+ years of Solutions Engineering (or similar Sales Engineering roles) experience.
- Familiarity (work experience) with Python, scripting, etc.
- Familiarity with AI frameworks.
- Effective time management and capable of balancing multiple tasks.
- Ability to communicate ideas clearly through documents, presentation, etc.
Responsibilities
- Lead on NVIDIA software products within a focused account team, assisting large customers and cloud providers in developing new workflows using NVIDIA technologies (hardware and software).
- Work closely with outstanding engineering and product teams to tackle tough problems and bring NVIDIA solutions to market in customer products and workflows.
- Become a trusted advisor for the customer by understanding their environment, constraints, and business models and then translate those into product requirements and solutions to solve their problems applying NVIDIA technologies.
- Conduct regular technical customer meetings for project/product details, feature discussions, introductions to new technologies, and debugging sessions.
- Work with customers to build PoCs for solutions to address critical business.
- Prepare and deliver technical content to customers including presentations, workshops, etc.
Preferred Qualifications
- External customer facing skill-set and background
- Hands-on experience developing AI applications using NVIDIA technologies (GPUs and/or software)
- Cloud experience (applying cloud concepts like Database, etc. in developing workflows for customer use cases)
- Hands-on experience with GPU systems in general including but not limited to AI workflow development, performance development, AI benchmarking, etc.