Senior High Performance AI Engineer, Agentic AI

NVIDIA•Austin, CA

10d

About The Position

We are looking for outstanding Senior High Performance AI Engineers to build the next generation of agentic AI systems for the CUDA ecosystem. Our team works across the full agentic AI stack—from training and improving models, to designing agent architectures and multi-agent systems, to building the systems, runtimes, and evaluation frameworks that make them effective at scale. You will help develop intelligent agentic systems that can reason about, generate, optimize, and operate across NVIDIA's accelerated computing stack. This includes advancing model and agent capabilities, building scalable agent systems and runtimes, developing high-fidelity training and evaluation environments, and co-designing with NVIDIA's libraries, runtimes, compilers, and hardware. You will collaborate closely with internal NVIDIA software, model, and hardware teams to bring new capabilities into NVIDIA products.

Requirements

Bachelor's degree in Computer Science, Electrical Engineering, or a related field, or equivalent experience; MS or PhD preferred.
4+ years of relevant industry or academic experience in AI systems, machine learning, compilers, high-performance computing, or related areas.
Hands-on experience in one or more of the following: agent systems, coding agents, reinforcement learning, or modern AI inference systems.
Strong C/C++, Rust, and Python programming skills, with solid software engineering fundamentals.
Experience with GPU programming and performance optimization using CUDA or comparable accelerator platforms, and the ability to work effectively across system boundaries.

Nice To Haves

Track record of building high-impact coding agents, autonomous software-engineering systems, or developer tools.
Hands-on experience optimizing and deploying with TRT-LLM, SGLang, vLLM, or Transformer Engine.
Deep expertise in GPU systems and performance optimization, demonstrated through benchmark results, deployed systems, publications, or widely used software.
Publications or open-source leadership in deep learning, agentic AI, reinforcement learning, compilers, high-performance computing, or AI systems.

Responsibilities

Design, build, and optimize agentic AI systems for the CUDA ecosystem, including agent architectures, multi-agent workflows, tool use, memory, and orchestration.
Build the data, environments, verification, reward, and evaluation systems needed to continuously improve model and agent capabilities.
Co-design and optimize agentic systems across NVIDIA's software and hardware stack, from models and inference through compilers, runtimes, libraries, kernels, and GPUs.