We are looking for an experienced Software Engineer to develop our core libraries for Agentic Applications. 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. Responsibilities: 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. Requirements: 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. Nice to have: 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.