Senior Software End-to-End Architect

About the role

NVIDIA is looking for a senior, hands‑on End‑to‑End Architect to shape system architecture for next‑generation AI and accelerated computing platforms. You will own the full lifecycle of large‑scale solutions that integrate networking, software, hardware, infrastructure and applications.

Key responsibilities

• Define end‑to‑end system architectures for Spectrum‑X solutions, covering networking, software, hardware, infrastructure and application integration.
• Lead architecture activities from requirements gathering through implementation, validation, deployment and optimization.
• Collaborate with systems, software, model, networking, platform and application teams to deliver high‑performance integrated solutions.
• Evaluate and integrate new software and hardware technologies such as load balancing, telemetry and congestion control.
• Translate product and business requirements into architectural specifications, component interfaces and execution plans.
• Identify gaps, dependencies, trade‑offs and performance bottlenecks across the system.
• Work with productization teams to ensure reliability, scalability and production readiness.
• Produce architecture documents, design specifications and technical publications.

Required profile

• Bachelor’s, Master’s or PhD in Computer Science, Electrical Engineering or equivalent experience.
• 5+ years of experience in software architecture, systems engineering or large‑scale performance‑critical systems.
• Strong background in high‑performance networking, distributed systems and networked applications.
• Deep understanding of deep‑learning systems, GPU acceleration and AI model execution flows.
• Proven track record delivering end‑to‑end architectures spanning software, hardware, networking and infrastructure.
• Experience leading complex technical initiatives in multi‑functional environments.
• Excellent communication and technical leadership skills.

Required skills

• High‑performance networking
• Distributed systems
• Networked applications
• Deep learning systems
• GPU acceleration
• AI model execution flows
• Load balancing
• Telemetry
• Congestion control