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.
NVIDIA is seeking a Senior Software Engineer to help build the Agent Intelligence (AIQ) toolkit, an open-source library for connecting enterprise agents to data sources and tools across any framework. In this role, you’ll be at the forefront of agentic application development, working with the latest LLM frameworks and libraries to create a powerful toolkit that enables large-scale AI agents for modern enterprises. You’ll design tracing and profiling tools to help scale these applications and collaborate with experts across domains to optimize performance, using the full power of the NVIDIA stack. Together, we’ll push the boundaries of NVIDIA’s core frameworks, revolutionizing AI applications for our enterprise customers!
What you'll be doing:
Implementing new features of our GenAI SDKs that enable LLM agents to expand to new, more demanding use cases and larger deployment configurations.
Crafting proof-of-concept workflows rooted in first principles that apply modern data science techniques to GenAI use cases.
Collaborating with other engineers to develop new optimizations for agentic applications across the entire data center, which focus on improving accuracy, reducing latency, and growing efficiency.
Building integrations between the AIQ toolkit and other NVIDIA products and services, such as the NeMo Framework, NIMs, and NVIDIA Blueprints.
Working with data scientists and ML/DL engineers to move from proof-of-concept analysis and modeling to production-ready pipelines and deployments.
What we need to see:
BS in Computer Engineering, Computer Science, Data Science, or other closely related field (or equivalent experience).
Proficient in Python, with at least 5+ years of experience building Python libraries or applications for enterprise customers.
Experience with GenAI application development using LLM frameworks (such as Langchain, Llamaindex, or AutoGen), evaluation systems (such as RAGAs), and observability platforms (such as Arize Phoenix, W&B Weave, or LangSmith).
Understanding of different agent architectures, RAG systems, and communication protocols (such as MCP or Google A2A).
Deep desire to solve complex engineering challenges with efficiency as a priority.
Ability to quickly learn and apply new technologies and libraries.
Self-starter with a proactive attitude, capable of working independently and effectively within a distributed team.
Excellent communication skills, essential for collaboration with multi-functional teams.
Ways to stand out from the crowd:
MS, PhD or equivalent experience in Computer Engineering, Computer Science, Data Science, or other closely related field.
Experience developing for GPU platforms and familiarity with NVIDIA technologies (e.g., CUDA, TensorRT, Triton, NeMo) and LLM serving frameworks (e.g., Dynamo, vLLM, SGLang).
Proficient in distributed systems and communication frameworks (e.g., Ray, Dask, Spark, gRPC, Kafka, nats.io).
Proven ability to prototype and productionize features, including deploying large-scale agentic applications with high concurrency.
Track record of contributing to open-source Python projects.
You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
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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.”
