Solutions Architect, Generative AI at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial IntelligenceIndustries

Requirements

MSc, PhD in Computer Science, Electrical Engineering, Software Engineer, ML Engineer, or related fields (or equivalent experience)
5+ years of relevant work experience in developing and 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 generative models
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

Responsibilities

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. 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
Define the scope, success metrics, and evaluation criteria for partner-led customer projects, ensuring they are built on standardized and reproducible GPU-accelerated workflows
Enable strategic partners to launch their own Professional Services and platforms by tailoring NVIDIA agentic AI blueprints for high-impact customer workloads. 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

Skills

Key technologies and capabilities for this role

Generative AISolutions ArchitectureCUDANeMoTritonGPU SystemsReference ArchitecturesPrototypesAI DeploymentPartner Enablement

Questions & Answers

Common questions about this position

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

Candidates need an MSc or PhD in Computer Science, Electrical Engineering, Software Engineering, ML Engineering, or related fields (or equivalent experience), plus 5+ years of relevant work experience in developing and deploying AI models at scale as a Software Engineer or deep learning engineer.

What technical skills are essential for this position?

A consistent track record of building enterprise-grade agentic AI systems using open-source models, solid foundation in deep learning with emphasis on generative models, and hands-on experience with LLM and agentic frameworks like NeMo Agent Toolkit, LangChain, Semantic Kernel, Crew.ai, and AutoGen are required.

What is the salary or compensation for this role?

This information is not specified in the job description.

Is this position remote or does it require office work?

This information is not specified in the job description.

What is the company culture like for this team at NVIDIA?

The team offers a diverse, supportive environment where everyone is inspired to do their best work, acting as trusted advisors and technical partners to the ecosystem.

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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