Solutions Architect, Agentic AI at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial IntelligenceIndustries

Requirements

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
Clear written and oral communication skills with the ability to effectively collaborate with executives and engineering teams

Responsibilities

Deliver innovative and optimized AI agents using the latest techniques including Test Time Compute, Reinforcement Learning, inference optimization, and model fine-tuning
Engineer new solutions to fit customer needs by integrating their enterprise data sources into meaningful agentic applications
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 deeply with engineering teams, stay ahead of the latest AI advancements, and apply strong technical judgment to everything delivered
Provide direct feedback from first-time implementations to improve software products
Scale knowledge by educating vertical teams and building communities on NVIDIA AI software products

Skills

Key technologies and capabilities for this role

PythonC/C++Deep LearningMachine LearningReinforcement LearningTest Time ComputeInference OptimizationModel Fine-TuningGenerative AI

Questions & Answers

Common questions about this position

What education and experience are required for this Solutions Architect role?

A BS, MS, or Ph.D. in Engineering, Mathematics, Physics, Computer Science, Data Science, or similar (or equivalent experience) is required, along with 5+ years of experience in Deep Learning and Machine Learning.

What technical skills are essential for this position?

Strong software engineering skills with Python, C/C++, and Linux are required, plus experience with GPUs and deep learning frameworks like TensorFlow or PyTorch, and building multi-agent systems using libraries like LangGraph, LlamaIndex, or CrewAI.

Is this a remote position, or does it require office work?

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

What makes a candidate stand out for this Solutions Architect position?

Candidates stand out with expertise in building evaluation harnesses, success metrics, automated testing pipelines, and guardrail frameworks; skills in fine-tuning and optimizing LLMs/SLMs including prompt engineering and quantization; and experience with production-grade deployment patterns using Kubernetes.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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