Want to join a team that's revolutionizing the field of AI with data center scale solutions? We are seeking a highly technical Solution Architect to serve as a forward-deployed technical liaison between NVIDIA’s Partner Network (NPN), NVIDIA’s internal teams, and enterprise customers. In this role, your focus will be to provide deep hands-on networking expertise with solution build, automation, and customer-facing consulting to deploy large-scale AI factories. As Solution Architects on the NVIDIA Partner Network team, we are actively helping NVIDIA AI Factory solutions bring the benefits of large scale AI to customers through our partners. We work closely with partners to address unsolved problems in the industry and help to deploy and operationalize AI solutions at scale!
What you will be doing:
Providing Ethernet and routing expertise to customers during project delivery to design, architect and test Ethernet networking solutions
Working on multi-functional teams to provide Ethernet network expertise to server infrastructure builds, accelerated computing workloads and GPU enabled AI applications
Crafting and evaluating DevOps automation scripts for network operations, crafting architectures, and developing switch fabric configurations.
Implementing tasks related to network configuration and validation for data centers. Creating Methods of Procedure and deployment documents
Interacting with customers to obtain required information to design and build an optimal solution. Validating network architectures and configs in the lab
Use software tools to validate and monitor network performance
What we need to see:
Bachelor’s degree in engineering, or related field (or equivalent experience). Preferred qualifications include an advanced degree with 8+ years of proficiency in networking, data center architecture, and relevant certifications.
Strong Switching and Routing hands-on experience including BGP, VxLAN and EVPN Network fixing using a Sniffer (8+ years)
Strong Linux administration expertise with understanding of system-level issues, kernel drivers, PCIe devices, and computer hardware architecture (8+ years)
Engages with clients for network requirement analysis, builds next-gen data center network architectures, and validates functionality through simulations. Extensive experience in consulting or/and technical support(6+ years)
Background in datacenter engineering, CLOS networking architecture, or cloud applications is advantageous (4+ years)
Plays a pivotal role in automation, delivering fully automated network provisioning solutions using Ansible, Salt, and Python. (3+ years)
Strong abilities with technical presentations, providing partners training.
Able to travel (25%) as well as work non-standard working hours like during nights and weekends when needed
Ways to Stand out from the crowd:
Experience with Kubernetes and Docker
Familiarity with networking digital simulations, experience with NVIDIA Air, GNS3, EVE-NG Experience with network and server management tools like Grafana, Prometheus, Datadog, etc.
Personal Git repository with examples of coding expertise in Python
Experience with AI tools to boost work quality and meet project timelines
Strong channel sales and services knowledge and partner co-selling experience
This role embodies the forward-deployed engineer approach: you will spend significant time embedded with customer and partner technical teams. You will move fluidly between field deployments and internal NVIDIA collaboration. Your success is measured by the successful deployment and optimization of AI factories that enable customers and partners to achieve their AI ambitions. You will also provide critical feedback to refine NVIDIA’s reference architectures and partner enablement programs!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.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
- Bachelor's degree in engineering, or related field
- 8+ years of proficiency in networking and data center architecture
- Strong Switching and Routing hands-on experience including BGP, VxLAN and EVPN
- Strong Linux administration expertise
- 6+ years of consulting or technical support experience
- Background in datacenter engineering
- 3+ years of delivering automated network provisioning solutions
- Able to travel (25%)
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.”
