Senior Software Engineer, Agentic Engineering

## About the Role The Senior Software Engineer position at NVIDIA's Agentic Engineering team offers a rare opportunity to work at the intersection of modern AI and engineering. As part of the Deep Learning Framework Group, you will be responsible for developing agentic workflows that automate code generation, testing, and tuning across NVIDIA's frameworks, compilers, and developer tooling. Your work will have a direct impact on NVIDIA's early-adopter engineering teams, who are pushing the boundaries of AI innovation.

The Agentic Engineering team is a newly formed group within NVIDIA, and as a Senior Software Engineer, you will play a key role in shaping the team's technical direction. You will work closely with cross-functional teams to identify areas where agentic workflows can have the highest impact and develop solutions that meet their needs.

## What You Will Do - Develop a deep understanding of NVIDIA's early-adopter engineering teams and their requirements - Identify friction points where agentic workflows can have the highest impact - Design and develop agentic workflows that automate code generation, testing, and tuning - Collaborate with cross-functional teams to integrate agentic workflows into existing frameworks and tooling - Use technical judgment to distinguish durable architectural opportunities from short-term hype - Develop and maintain large-scale software systems, including multi-agent orchestration frameworks - Work with NVIDIA's latest GPUs to develop and optimize AI-powered workflows - Participate in code reviews and contribute to the improvement of the team's codebase - Collaborate with the team to develop and maintain internal tools and frameworks - Stay up-to-date with the latest developments in AI, ML, and software engineering

## What We Are Looking For - MS in Computer Science, Engineering, or equivalent experience - 6+ years of experience in software engineering, with a focus on AI, ML, or related fields - Strong Python development skills, with experience in developing large-scale software systems - Working knowledge of GPUs or other highly data-parallel systems - Demonstrated experience with AI systems, including development, deployment, and maintenance - Strong understanding of software engineering principles, including design patterns, testing, and deployment - Experience with multi-agent orchestration frameworks, such as LangChain or LangGraph - Familiarity with compiler infrastructure, intermediate representations, or program transformation - Experience with autonomous search or optimization over high-dimensional parameter spaces

## Nice to Have - Experience building evaluation or testing harnesses, especially for ML systems or multi-agent workflows - Track record of building internal tools or frameworks that force-multiply engineering teams - Demonstrated ability to thrive in ambiguous, self-directed environments while remaining humble - Passion for following the evolution of ML hardware and staying up-to-date on emerging kernel programming techniques

## Benefits and Perks - Competitive base salary, determined based on location, experience, and pay of employees in similar positions - Equity and benefits package, including health, retirement, and other perks - Opportunity to work with a talented team of engineers and researchers - Flexible work arrangements, including remote work options - Access to the latest NVIDIA hardware and software tools - Professional development opportunities, including training, mentorship, and conference attendance - Recognition and rewards for outstanding performance and contributions

- Highlight your experience with AI and ML: Showcase your experience with AI and ML, including development, deployment, and maintenance of AI-powered systems.

• Emphasize your software engineering skills: Demonstrate your understanding of software engineering principles, including design patterns, testing, and deployment.
• Prepare to talk about your experience with GPUs: Be ready to discuss your experience with GPUs, including development, optimization, and deployment of GPU-accelerated workflows.
• Showcase your ability to work in ambiguous environments: Highlight your ability to thrive in self-directed environments, including your experience with remote work and autonomous decision-making.
• Be prepared to discuss your passion for ML and AI: Share your passion for ML and AI, including your experience with emerging technologies and trends in the field.
• Research NVIDIA's culture and values: Familiarize yourself with NVIDIA's culture and values, including its commitment to innovation, teamwork, and customer satisfaction.
• Practice your coding skills: Prepare for technical interviews by practicing your coding skills, including Python, C++, and other relevant programming languages.