NVIDIA is looking for Senior Solution Architect, Networking and compute Infrastructure to join its NVIDIA Infrastructure Specialist Team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centres. Join the team building many of the largest and fastest AI/HPC systems in the world! We are looking for someone with the ability to work on a dynamic customer focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners and internal teams, to analyse, define and implement large scale Networking projects. The scope of these efforts includes a combination of Networking, System Design and Automation and being the face to the customer!
What You'll Be Doing:
Primary responsibilities will include building AI/HPC infrastructure for new and existing customers.
Support operational and reliability aspects of large-scale AI clusters, focusing on performance at scale, real-time monitoring, logging, and alerting.
Engage in and improve the whole lifecycle of services—from inception and design through deployment, operation, and refinement.
Develop tooling to automate and manage of large-scale infrastructure environments, to automate operational monitoring and alerting, and to enable self-service consumption of resources.
Deploy monitoring solutions for the servers, network and storage.
Perform troubleshooting bottom up from bare metal, operating system, software stack and application level.
Being a technical resource, develop, re-define and document standard methodologies to share with customer and internal teams Support activities and engage in POCs/POVs for future improvements.
Experience with system administration on Linux systems required (CentOS, RHEL, and Ubuntu preferred)
What We Need to See:
BS/MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields with at least 5+ years’ work or research experience in networking fundamentals, TCP/IP stack, and data centre compute architecture.
Advance knowledge of HPC, AI & EVPN, BGP, OSPF, VXLAN protocols.
Deep understanding of DC architecture fundamentals such as compute, storage (PFS) & InfiniBand, Ethernet, NVLink.
Experience running HPC performance benchmarks, cluster health checks, and profiling tools to identify infrastructure bottlenecks.
Python programming, bash scripting experience and Advance Linux knowledge.
Extensive experience delivering automated network provisioning and comfortable with automation and configuration management tools including Jenkins, Ansible, Puppet. Chef, etc.
Possess solid working knowledge of Ethernet/InfiniBand/RDMA core principles.
Excellent customer-facing and communication skills (verbal and written in both languages), enabling effective engagement with customers, partners, and cross-functional teams across the India region. Listening skills in English are critical.
Willingness to travel
Ways To Stand Out from The Crowd:
Knowledge of CPU and/or GPU architecture including of Kubernetes, container related microservice technologies.
Background with RDMA (InfiniBand or RoCE) fabrics.
Linux or Networking Certifications (e.g., CCNP, CCIE) or NVIDIA-related certifications.
Deep Knowledge on observability stack and build experience.
Skills Required
- BS, MS, PhD, or equivalent experience in Computer Science, Data Science, Electrical or Computer Engineering, Physics, Mathematics, or another engineering field
- At least 5 years of work or research experience in networking fundamentals, TCP/IP, and data center compute architecture
- Advanced knowledge of HPC, AI, EVPN, BGP, OSPF, and VXLAN
- Deep understanding of compute, storage, parallel file systems, InfiniBand, Ethernet, and NVLink
- Experience with HPC performance benchmarks, cluster health checks, and profiling tools
- Python programming and Bash scripting experience
- Advanced Linux knowledge and system administration experience; CentOS, RHEL, and Ubuntu preferred
- Experience delivering automated network provisioning
- Experience with Jenkins, Ansible, Puppet, Chef, or similar automation and configuration management tools
- Working knowledge of Ethernet, InfiniBand, and RDMA principles
- Excellent customer-facing and written and verbal communication skills
- Willingness to travel
- Knowledge of CPU or GPU architecture, Kubernetes, and container-related microservice technologies
- Background with RDMA fabrics, including InfiniBand or RoCE
- Linux, networking, or NVIDIA-related certifications, such as CCNP or CCIE
- Deep knowledge of observability stacks and experience building them
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.”
