Senior Staff Software Engineer — Agentic AI Applications and Foundations at NVIDIA

Department: Engineer, Sys SW

Compensation

$224,000 – $431,250/yr

Setup: On-site
Location: California
Type: Full-time
Level: staff+
Posted: Sep 28, 2026

Description

NVIDIA is hiring a senior staff-level full-stack engineer to harden and architect production AI agent infrastructure across desktop, web, and service-based products. The role focuses on reliability, performance, observability, release confidence, security, distributed systems, testing, CI/CD, incident response, and reusable platform capabilities, while partnering with AI, product, infrastructure, and research teams. Candidates need a BS, MS, or equivalent in computer science or a related field, at least 12 years of production software experience, and expertise across frontend, backend, platform, and AI application patterns.

Required Skills

Full-stack
TypeScript
React
Python
Go
Distributed systems
CI/CD
Observability
Incident response
RAG
MCP integrations

Additional Information

Minimum Education: Bachelor of Science, Master of Science, or equivalent experience in Computer Science or a related field
Required Previous Experiences: 12+ years building and operating production software systems, including significant architecture and delivery leadership across the full stack
Enterprise application deployment, security, authentication, device management, and application lifecycle management
Frontend, backend, and platform application development
Taking complex products from prototype to reliable, secure, well-operated production systems
Testing strategy, release engineering, observability, performance tuning, and incident response
Building shared services, internal platforms, SDKs, or core infrastructure for multiple teams or products
Hardening desktop or client applications at scale
Building reusable infrastructure for AI products
Identity, discovery, trust, reputation, or graph-based systems for large-scale agent collaboration
GPU-accelerated systems or NVIDIA AI technologies
Preferred Qualifications: Experience hardening desktop or client applications at scale
Improving engineering velocity and consistency through frameworks, platform services, design patterns, and developer tooling
Building reusable infrastructure for AI products
Familiarity with identity, discovery, trust, reputation, or graph-based systems
Experience with GPU-accelerated systems or NVIDIA AI technologies
Translation Company Name: NVIDIA