Senior Solutions Architect, Agentic 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

N/AIndustries

Requirements

MS or PhD degree in Computer Science/Engineering, Machine Learning, Data Science, Electrical Engineering or a closely related field (or equivalent experience)
8+ 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 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
Ways to stand out (Preferred)
Demonstrate expertise in building applications and systems using NeMo Framework, inference at scale, NIMs, AI Blueprints
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 or Google A2A)
NVIDIA GPUs and system software stack

Responsibilities

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. 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

Agentic AI

Generative AI

CUDA

NeMo

Triton

GPU systems

AI agents

reference architectures

AI prototypes

production scaling

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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