NVIDIA is seeking an outstanding AI Engineer or Solutions Architect to join our growing team focused on ecosystem partner enablement for Generative AI. In this role, you will lead by example, acting as both a strategic technical expert and a hands-on developer. You will directly build innovative proof-of-concept solutions and reference architectures for innovative AI agents, demonstrating the full power of the NVIDIA full-stack accelerated Generative AI platforms. By developing these foundational solutions, you will provide partners with the technical blueprints and expert guidance needed to architect and deploy their own transformative applications using NVIDIA full AI stack, from GPU systems and CUDA to NeMo and Nemotron.
The Generative AI Partners Enablement Solutions Architect team is committed to leveraging advanced technologies to address and expedite the deployment of solutions for customers' real-world challenges. We act as trusted technical advisors and partners to our ecosystem. As a member of NPN Generative AI Solution Architecture team, you will be immersed in a diverse, supportive environment where everyone is inspired to do their life’s work. Come join the team and see how you can make a lasting impact on the world by applying accelerated computing AI and solve category defining systems and production grade AI solutions at scale.
What you will be doing:
Building an end-to-end agentic AI applications that solve real-world enterprise problems across various industries.
Serve as the primary technical domain expert for pre- and post-sale for partners, embedding deeply with them to design and deploy Generative AI solutions at scale. Maintain strong relationships with leadership and technical teams to drive adoption, and successful utilization of NVIDIA GenAI platforms.
Accelerate partner/customer time to value by providing repeatable reference architecture guidance, building hands-on prototypes, and advising on standard methodologies for scaling solutions to productions.
Establish the scope, success metrics, and evaluation criteria for partner-led customer projects, ensuring alignment to standardized and reproducible GPU-accelerated workflows.
Enable strategic partners to build their own Professional Services, platforms and products by integrating and accelerating using NVIDIA technologies for high-impact customer workloads. You will proactively find opportunities to drive deeper adoption and utilization of NVIDIA's Generative AI products.
Codify knowledge and operationalize technical success practices to help partners scale impact across industries and workloads.
What we need to see:
MS or PhD degree in Computer Science/Engineering, Machine Learning, Data Science, Electrical Engineering or a closely related field (or equivalent experience).
5+ years of meaningful work experience in deploying AI models at scale as a Software Engineer or Deep Learning engineer.
Consistent track record of building enterprise-grade agentic AI systems using open-source models and solid foundation in deep learning, with a particular emphasis on LLM and VLM.
Hands-on experience with LLM and agentic frameworks (NeMo Agent Toolkit, LangChain, Semantic Kernel, Crew.ai, AutoGen) and evaluation and observability platforms. Comfortable building prototypes or proofs of concept
Strong coding development and proficiency in Python, C++ and Deep Learning frameworks (PyTorch, or TensorFlow).
Excellent communication and presentation skills to effectively collaborate with both internal executives, partners and customers.
Ways to stand out from the crowd:
Demonstrate expertise in building applications and systems using NeMo Framework, Nemotron, Dynamo, TensorRTLLM, NIMs, AI Blueprints. And actively contribute to the open-source community.
Take end-to-end ownership of projects, proactively acquiring new skills or knowledge as needed to drive success.
Excel in fast-paced environments, adeptly managing multiple workstreams and prioritizing for the highest customer impact.
Understanding of different advanced agent architectures and emerging communication protocols (MCP, OpenAI Agentic SDK, or Google A2A).
NVIDIA GPUs and system software stacks (e.g. NCCL, CUDA), as well as HPC technologies such as InfiniBand, MPI, NVLink and others.
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
- MS or PhD in Computer Science/Engineering, Machine Learning, Data Science, Electrical Engineering or related field
- 5+ years of experience in deploying AI models at scale
- Experience building enterprise-grade AI systems using LLM and VLM
- Hands-on experience with LLM frameworks
- Proficiency in Python and C++
- Excellent communication skills
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.
-
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.
-
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.
-
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.”
