Do you want to drive the future of AI by building agentic AI applications at scale? We are looking for Solution Architects to join the NVIDIA AI Enterprise (NVAIE) SA Segment Team to help redefine how enterprises build and deploy AI agents. We specialize in the newest technology and advances in Machine Learning, Deep Learning and Generative AI. The vision of the NVAIE Segment team is to use our deep expertise to guide and enable the successful adoption at scale of NVIDIA AI Enterprise Software in production!
What you’ll be doing:The Agentic AI team mission is to deliver innovative and optimized AI agents using the latest techniques including Test Time Compute, Reinforcement Learning, inference optimization and model fine-tuning. We specialize on engineering new solutions to fit our customers needs by integrating their enterprise data sources into meaningful agentic applications.
You’ll work with agentic frameworks to develop applications that retrieve and generate insights from enterprise data, including text, code, and images. Your focus will be on creating high-impact solutions such as deep research assistants, multi-modal dialogue systems, and task-specific agents that support a wide range of enterprise workflows. You’ll be deeply engaged with engineering teams, stay ahead of the latest AI advancements, and apply strong technical judgment to everything you deliver.
Provide direct feedback from these first-time implementations to improve our software products and scale knowledge by educating vertical teams and building communities on NVIDIA AI software products!
Strong foundational expertise, from a BS, MS, or Ph.D. degree in Engineering, Mathematics, Physics, Computer Science, Data Science, or similar (or equivalent experience).
5+ years experience demonstrating an established track record in Deep Learning and Machine Learning. Strong software engineering and debugging skills, including experience with Python, C/C++, and Linux. Experience with GPUs as well as expertise in using deep learning frameworks such as TensorFlow or PyTorch.
Proficiency in rapid prototyping using Python with strong foundational knowledge of data structures, algorithms, and software engineering principles.
Experience with building advanced multi-agent systems, using libraries like LangGraph, LlamaIndex, CrewAI.
Ability to multitask effectively in a dynamic environment, as well as clear written and oral communications skills with the ability to effectively collaborate with executives and engineering teams.
Expertise in building evaluation harnesses, success metrics, automated testing pipelines, and guardrail frameworks to ensure agentic AI workflows are safe, reliable, and production-ready.
Skilled in fine-tuning and optimizing reasoning-focused LLMs and SLMs, including prompt engineering, quantization, and benchmarking.
Experience developing production-grade deployment patterns using Kubernetes/OpenShift, CI/CD automation, and secure cloud-native infrastructure.
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
- BS, MS, or Ph.D. degree in Engineering, Mathematics, Physics, Computer Science, Data Science, or similar
- 5+ years experience in Deep Learning and Machine Learning
- Strong software engineering and debugging skills, experience with Python, C/C++, and Linux
- Experience with deep learning frameworks such as TensorFlow or PyTorch
- Ability to multitask effectively in a dynamic environment
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.”
.jpg)
