NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
We are looking for an experienced Software Engineer to develop our core libraries for Agentic Applications. Are you excited by the prospect of building foundational technology that powers the next generation of agents? Have you ever dreamed of elevating engineering practices to enable the safe and scalable deployment of autonomous systems? As a global leader in AI and deep learning, NVIDIA is redefining industries and our work in agentic computing is at the forefront of this revolution. Join us in building the scalable agentic capabilities, reusable building blocks, and high-quality libraries that will accelerate developer productivity, ensure agent quality, and provide critical acceleration and optimization for highly performant and efficient agents. Work directly with a community of creative engineers and collaborate on projects that push the boundaries of what's possible in the world of autonomous agents!
What you'll be doing:
Track and understand evolving agent development patterns across NVIDIA and the broader ecosystem, maintaining current knowledge of both research and commercial products.
Develop open-source libraries and tools which accelerate and optimize agent harnesses and frameworks ensuring top-tier performance, accuracy, quality, and stability.
Benchmark the latest agents to identify bottlenecks and build creative solutions to increase performance, reduce cost, and improve latency.
Work closely with teams building high-performance data pipelines, RAG systems, vector databases, and GPU-optimized training and inference workflows to deliver best-in-class agentic applications.
Identify gaps and friction in current agent architectures, and translate insights into agentic tools that boosts developer velocity and agent quality—backed by evaluations, benchmarking, and feedback loops.
What we need to see:
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Applied Math, or a related field, or equivalent experience.
8+ years experience in at least one of Rust, Python, Go, or Node.js, with working familiarity in at least one more.
Solid understanding of asynchronous programming, callbacks, request lifecycles, and event-driven systems.
Hands-on experience with evolving agent architectures, multiple agents frameworks and agent harnesses.
Proficiency in LLM applications, agent workflows, tool calls, and model-provider APIs.
Ability to design or extend cross-language APIs with attention to consistency, usability, stability, and backwards compatibility.
Systems-level debugging and performance intuition: able to trace execution from high-level API calls through runtime internals, language bindings, callbacks, serialization, and event emission to understand overhead and optimize hot paths.
Strong interpersonal skills, enabling direct contact and effective collaboration with the open source community.
Ways to stand out from the crowd:
Experience building evaluation/benchmarking systems for agent workflows (metrics, regression, feedback loops).
Rust systems work, especially async Rust, Tokio, serde, API design, or runtime state management and /or Python native extension experience with PyO3, maturin, or Python/Rust bindings.
Instrumenting third-party frameworks without changing user-visible behavior. Knowledge of OpenTelemetry, tracing, structured events, exporters, or observability pipelines are a plus.
Middleware, plugin systems, guardrails, policy engines, or request/response interception and maintaining open-source libraries, SDKs, or internal developer platforms.
Profiling or optimizing runtime/library overhead across language boundaries, async execution, native bindings, serialization, tracing, or middleware pipelines.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.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.”
