Solutions Architect

NVIDIA

Solutions Architect driving innovative AI applications at NVIDIA for enterprise needs. Focused on building agentic frameworks and deploying AI agents with cutting-edge technologies.

Posted 6/29/2026full-timeSanta Clara • California • 🇺🇸 United StatesMid-LevelSenior💰 $152,000 - $241,500 per yearWebsite

Tech Stack

Tools & technologies

LinuxPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Deliver innovative and optimized AI agents using the latest techniques including Test Time Compute, Reinforcement Learning, inference optimization and model fine-tuning.
Work with agentic frameworks to develop applications that retrieve and generate insights from enterprise data, including text, code, and images.
Create high-impact solutions such as deep research assistants, multi-modal dialogue systems, and task-specific agents that support a wide range of enterprise workflows.
Engage with engineering teams, stay ahead of the latest AI advancements and apply strong technical judgment to deliverables.
Provide direct feedback from first-time implementations to improve software products and scale knowledge by educating vertical teams and building communities on NVIDIA AI software products.

Requirements

What you’ll need

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.

Benefits

Comp & perks

equity
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Hard Skills & Tools

Reinforcement LearningInference OptimizationModel Fine-TuningSoftware EngineeringDebuggingData StructuresAlgorithmsRapid PrototypingAI Agent DevelopmentEnterprise Data Insights

Soft Skills

Clear CommunicationCollaborationMultitasking