NVIDIA is leading the next era of AI computing, bringing AI from the cloud to local devices. The Windows Client AI team develops the software platform that enables developers, enterprises, and creators to build and run AI applications on NVIDIA client platforms, including GeForce RTX PCs, RTX PRO workstations, RTX Spark, DGX Spark, and DGX Station.
We are looking for a highly technical Senior Technical Program Manager to lead the execution of NVIDIA's Windows Client AI software platform. In this role, you will work closely with engineering, product management, architecture, developer technology, and strategic partners to deliver the next generation of AI experiences on Windows. You will drive complex cross-functional programs spanning AI frameworks, inference runtimes, model optimization, Windows integration, developer tools, and AI applications. This is a highly visible role requiring technical depth, exceptional execution, and the ability to influence engineering decisions across multiple organizations.
What you'll be doing:
Drive end-to-end execution of the Windows Client AI software roadmap across globally distributed engineering teams, ensuring alignment, transparency, and predictable delivery.
Partner with product management and architects to translate product strategy into engineering plans, milestones, and successful releases with measurable outcomes.
Lead cross-functional programs influencing technical direction, trade-offs, and prioritization spanning AI frameworks, inference runtimes, model optimization, Windows integration, SDKs, and AI applications.
Work closely with engineering teams to identify technical risks, resolve cross-team dependencies, and drive execution from concept through release.
Collaborate with Microsoft, OEMs, ISVs, and internal teams to enable new AI capabilities across NVIDIA client platforms.
Drive planning and execution for emerging AI technologies, including LLMs, multimodal AI, AI agents, model optimization, and hybrid AI applications.
Communicate program status, milestones, risks, and key decisions to engineering leadership and executives.
Champion engineering best practices in planning, release management, and program execution across globally distributed teams.
What we need to see:
BS/MS in Computer Science, Computer Engineering, or equivalent experience.
8+ years of experience leading complex technical programs in software engineering, AI/ML infrastructure, developer platforms, or systems software.
Strong understanding of modern AI software stacks, including deep learning frameworks, inference engines, and AI developer workflows.
Excellent communication, organizational, and cross-functional leadership skills with a proven ability to influence across organizations.
Strong analytical and problem-solving skills, with experience driving large-scale software programs from concept to release.
Ways to stand out from the crowd:
Software engineering background with experience in C++, Python, or AI/ML systems.
Familiarity with modern AI inference technologies such as TensorRT, vLLM, PyTorch, ONNX Runtime, DirectML, or llama.cpp.
Experience with LLMs, multimodal AI, agentic AI, model optimization, or GPU acceleration.
Knowledge of Windows platform technologies, GPU architecture, CUDA, or NVIDIA AI software.
Experience collaborating with Microsoft, OEMs, ISVs, or contributing to open-source AI projects.
NVIDIA is widely considered one of the technology world's most desirable employers. We have some of the most forward-thinking engineers and researchers solving the hardest problems in AI computing. If you're passionate about AI, enjoy solving complex technical challenges, and thrive in a collaborative environment, we'd love to hear from you.
Skills Required
- BS/MS in Computer Science, Computer Engineering, or equivalent experience.
- 8+ years leading complex technical programs in software engineering, AI/ML infrastructure, developer platforms, or systems software.
- Strong understanding of modern AI software stacks, including deep learning frameworks, inference engines, and AI developer workflows.
- Excellent communication, organizational, and cross-functional leadership skills with proven ability to influence across organizations.
- Strong analytical and problem-solving skills; experience driving large-scale software programs from concept to release.
- Software engineering background with experience in C++, Python, or AI/ML systems.
- Familiarity with TensorRT, vLLM, PyTorch, ONNX Runtime, DirectML, or llama.cpp.
- Experience with LLMs, multimodal AI, agentic AI, model optimization, or GPU acceleration.
- Knowledge of Windows platform technologies, GPU architecture, CUDA, or NVIDIA AI software.
- Experience collaborating with Microsoft, OEMs, ISVs, or contributing to open-source AI projects.
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
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 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, NVIDIA is increasingly known as “the AI computing company.”
