NVIDIA is looking for a Senior Solutions Architect to work with our Global Systems Integrator partners and AI consulting partners. This role requires a combination of technical authority and proven experience operating within regional partnerships. This individual will help inspire our partners to reimagine, reinvent and operate the enterprise business processes of the world's largest companies using Agentic AI using the NVIDIA platform. This is a highly technical role that requires deep expertise in generative AI, large language models (LLMs), and scalable software engineering practices. Our goal is to develop long-lasting relationships with our technology partners, making NVIDIA an integral part of their solutions. We are looking for someone who is always thinking about artificial intelligence, someone who can maintain alignment in a fast paced and constantly evolving field.
As a Solutions Architect, you will be the first line of technical expertise between NVIDIA, our AI consulting partners and our end-customers. Your duties will vary from creating pilots, demos and MvPs, to building relationships with key technical teams to evangelize accelerated computing and Agentic AI. Dynamically engaging with developers, researchers, data scientists, IT managers and senior leaders is a meaningful part of the Solutions Architect role, to identify challenges and create solutions.
What You'll be Doing:
Becoming an expert and enabling GSI developers to adopt NVIDIA Agent Toolkit, Nemotron and NIM for their AI offerings, platforms and client services.
Construct complex AI agent workflows to analyse, strategise, perform tasks, access APIs, and fix errors autonomously.
Work with Partner Business Managers to thoughtfully craft actionable and effective strategies for the partnerships/alliances.
Closely partner with other Solutions Architects, engineering, product and business teams at NVIDIA to build AI full stack solutions for industry vertical and enterprise use cases.
Encourage industry executives and GSI leaders by articulating the business value of state-of-the-art AI solutions.
What We Need to See:
BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience)
5+ overall years in deep learning, data science or software development with knowledge of parallel computing with GPUs
Strong development expertise building RAG pipelines and Agentic AI applications.
Developer background with LangChain and LangGraph orchestrating LLMs
Clear written and oral communication skills with the ability to collaborate with management and engineering. Share knowledge with clients, partners and co-workers.
Excellent ability to listen understand and answer, asking questions and being comfortable with presenting visionary technical solutions in English
Ways to Stand Out from The Crowd:
Prior experience working with technical teams across multiple external stakeholders
Working proficiency with Orchestration platforms like Kubernetes and datacenter including compute, storage, and networking.
Expertise in NVIDIA platform-based development using Nemo and NIM, ML/DL frameworks and MLOps ecosystem of tools and solutions in the cloud and on-prem.
Background in cloud-based solution designing, APIs and Microservices, orchestration platforms, storage solutions and data migration techniques
Curiosity to dig into unfamiliar territories to tackle sophisticated problems and be a phenomenal listener.
Skills Required
- BS, MS, or PhD in Computer Science, Electrical or Computer Engineering, Physics, Mathematics, another engineering field, or equivalent experience
- 5+ years of experience in deep learning, data science, or software development
- Knowledge of parallel computing with GPUs
- Strong development experience building RAG pipelines and Agentic AI applications
- Development experience with LangChain and LangGraph for LLM orchestration
- Clear written and oral communication skills and ability to collaborate with management and engineering teams
- Ability to present technical solutions in English
- Experience working with technical teams across multiple external stakeholders
- Working proficiency with Kubernetes and datacenter compute, storage, and networking
- Experience with NVIDIA platform development using NeMo, NIM, machine learning and deep learning frameworks, and MLOps tools
- Background in cloud-based solution design, APIs, microservices, orchestration platforms, storage solutions, and data migration
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.”
