Senior Solutions Architect, Generative AI Deployment and AIOps

About the role

NVIDIA is seeking AI Solutions Architects to assist and support customers building solutions with NVIDIA's latest AI technology. This role involves working with various teams and customers on innovative projects.

Responsibilities

• Partnering with other solution architects, engineering, product, and business teams
• Understanding and addressing the technical needs of these teams
• Dynamically engaging with developers, scientific researchers, and data scientists across a range of technical areas
• Strategically partnering with key customers and industry-specific solution partners
• Collaborating with customers to help them adopt and build creative solutions using NVIDIA technology and MLOps solutions
• Analyzing performance and power efficiency of AI inference workloads on Kubernetes
• Travel to conferences and customers may be required (20%)

Requirements

• BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience)
• 8+ years of hands-on experience with Deep Learning frameworks such as PyTorch and TensorFlow
• Strong fundamentals in programming, optimizations, and software design, especially in Python
• Proficiency in problem-solving and debugging skills in GPU orchestration and Multi-Instance GPU (MIG) management within Kubernetes environments
• Experience with containerization and orchestration technologies, monitoring, and observability solutions for AI deployments
• Excellent knowledge of the theory and practice of LLM and DL inference
• Excellent presentation, communication, and collaboration skills

Qualifications

• BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience)
• 8+ years of hands-on experience with Deep Learning frameworks such as PyTorch and TensorFlow
• Strong fundamentals in programming, optimizations, and software design, especially in Python
• Proficiency in problem-solving and debugging skills in GPU orchestration and Multi-Instance GPU (MIG) management within Kubernetes environments
• Experience with containerization and orchestration technologies, monitoring, and observability solutions for AI deployments
• Excellent knowledge of the theory and practice of LLM and DL inference
• Excellent presentation, communication, and collaboration skills

Skills

• Experience with DL training at scale, deploying or optimizing DL inference in production
• Experience with NVIDIA GPUs and software libraries such as NVIDIA NIM, Dynamo, TensorRT, TensorRT-LLM
• Familiarity with parallel programming and distributed computing platforms
• Excellent C/C++ programming skills, including debugging, profiling, code optimization, performance analysis, and test design

Benefits

Base salary range: $184,000 - $287,500 USD. Eligible for equity and benefits. Applications accepted until April 10, 2026.

Note: NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer. We highly value diversity in our current and future employees.