Senior Staff Software Engineer — AI Applications and Platform Foundations

NVIDIA•Us, CA

About The Position

NVIDIA's invention of the GPU in 1999 sparked the growth of the PC-gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU-accelerated deep learning ignited modern AI—the next era of computing—with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” Our Enterprise AI team develops production-grade AI applications and shared AI platforms that operate across desktop, mobile, web, and cloud environments. These systems power engineering productivity, intelligent assistants, operational automation, enterprise search, knowledge management, and data-driven decision-making across NVIDIA. We are seeking a Senior Staff Software Engineer to help architect and build the foundation for NVIDIA's next generation of AI applications. This is a highly technical, hands-on leadership role for someone who combines deep full-stack engineering expertise with a strong platform technical leadership and a passion for delivering reliable, scalable, enterprise-grade AI products. This is not a research position. We are looking for an engineer who obsesses over software quality, operational excellence, user experience, and system reliability—and who can transform AI prototypes into trusted products used at scale.

Requirements

BS, MS, or equivalent experience in Computer Science, Software Engineering, or a related technical field.
10+ years of experience designing, building, and operating large-scale production software systems, including architecture leadership for complex products.
Strong full-stack development experience spanning modern frontend technologies (TypeScript/JavaScript, React, Electron, React Native, Flutter, or similar), backend services, APIs, and distributed systems.
Demonstrated expertise in cloud-native architectures, scalable platform infrastructure, data systems, and distributed application architectures.
Deep knowledge of software quality, testing, observability, release engineering, performance optimization, security, and operational excellence.
Experience building or operating AI-powered applications using technologies such as LLMs, RAG, agent frameworks, tool integrations, memory systems, or workflow orchestration.
Proven ability to influence technical direction across teams through strong architectural judgment, communication, and hands-on technical leadership.

Nice To Haves

Familiarity with enterprise application deployment, security, authentication, device management, and application lifecycle management.
Experience building and operating desktop and mobile applications at scale, including installers, enterprise deployment, app distribution, auto-update systems, crash recovery, offline experiences, and client observability.
Experience designing cross-platform application architectures that provide seamless user experiences across desktop, mobile, and web environments.
Familiarity with multi-agent systems, large-scale collaboration platforms, identity and trust frameworks, or enterprise-scale collaboration systems.
Hands-on experience with NVIDIA AI technologies, including NeMo, NIM, Nemotron, TensorRT-LLM, or AI Blueprints as well as experience contributing to or working with modern open-source AI ecosystems and agent frameworks.

Responsibilities

Architect and deliver production AI applications across desktop, mobile, web, and cloud platforms, driving technical decisions spanning user experiences, backend services, APIs, data pipelines, and platform infrastructure.
Establish engineering excellence for AI products through robust testing strategies, CI/CD, observability, release management, operational readiness, incident response, and performance optimization.
Build shared AI foundations including agent orchestration, memory and context services, evaluation frameworks, telemetry, workflow execution, tool integration, internal frameworks, and reusable platform services.
Operationalize NVIDIA AI technologies such as Nemotron, NIM, NeMo, AI Blueprints, and emerging AI platform capabilities in enterprise production environments.
Partner closely with product managers, designers, infrastructure teams, IT, and AI researchers to deliver measurable business impact while mentoring engineers and driving architectural alignment across organizations.