Principal Software Engineer

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 an inclusive, 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 to hire a deeply technical, creative, and hands-on Senior full-stack developer to build the next generation AI platforms and products that improve business efficiency and productivity.

This engineer is expected to be familiar with concepts of RAG, agentic AI to be able to build AI products using SOTA agentic paradigms, third party platforms and open-source repos. As a key leader in our technology team, you will play a pivotal role in shaping the architecture, development, and scaling of our software systems. This role will give an opportunity to collaborate with Cloud, AI/ML & Generative AI workforce in a multifaceted and agile working environment, while meeting the immediate and evolving needs of our business.

What you’ll be doing :

Hands-on experience with test automation, production testing, and automation frameworks

Solid understanding of Linux, embedded systems, firmware, and hardware/software integration

Integrate agents with enterprise data sources, APIs, and internal microservices to enable real-world actions. Collaborate with cross-functional teams to deliver end-to-end intelligent experiences across applications

Ensure reliability, safety, and performance of autonomous systems operating at scale

Architect and build agentic AI systems that leverage LLMs for reasoning, planning, and tool orchestration across enterprise workflows. Design and implement multi-agent frameworks enabling coordination, delegation, and dynamic task execution

Develop scalable platforms for retrieval-augmented generation (RAG), long-term memory, and contextual reasoning

Build reusable infrastructure for agent orchestration, tool integration, evaluation, and observability

Establish best practices for agent evaluation, guardrails, and human-in-the-loop workflows

Mentor engineers and provide technical leadership in designing complex distributed AI systems

Stay at the forefront of advancements in LLMs, agent frameworks, tool use, reasoning architectures, and open-source ecosystems

What we need to see:

BS, MS, or PhD in Computer Science, Electrical/Computer Engineering or related field (or equivalent experience)15+ years of experience building large-scale distributed systems and cloud-native applications (Python preferred)
Strong experience designing and deploying LLM-powered systems, including RAG, tool use, and agent-based architectures

Deep understanding of agentic AI paradigms (planning, memory, tool invocation, multi-step reasoning)

Experience with agent frameworks and orchestration tools (e.g., Lang Chain or similar)
Proven ability to design systems with high reliability, scalability, and performance

Hands-on experience deploying applications in Kubernetes environments. Experience building systems in cloud and hybrid environments

Strong programming skills across multiple languages and modern software stacks

Proven track record leading complex technical initiatives and mentoring high-performing teams

Excellent problem-solving, communication, and system design skills

Ways to stand out from the crowd:

Experience enhancing…