Senior System Software Engineer, Agentic Kernel Development
$184k - $357k • Remote • US, CA, Santa Clara
Posted 1mo ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Agent Engineer
About the job
NVIDIA's GPU SW Kernel organization is seeking a Senior System Software Engineer to develop the next generation of AI systems for GPU software development. This role focuses on crafting agentic AI systems to enhance the quality and efficiency of GPU software, transforming promising projects into critical infrastructure. You will be part of a dynamic team that significantly impacts GPU release quality and sets new standards for AI-driven automation.
Responsibilities
- Compose, build, and productize agentic AI systems that operate on GPU software artifacts like source code, crash dumps, and test results.
- Manage the full lifecycle of agentic services, from prototyping and evaluation to deployment and continuous improvement.
- Develop LLM-powered pipelines for code generation, automated bug triage, regression detection, and intelligent test coverage analysis.
- Build the agentic knowledge layer and MCP-based infrastructure for agents to interact with internal developer systems.
- Design and assess agent quality using metrics, evaluations, and precision/recall tradeoffs.
- Collaborate with GPU SW kernel engineers to identify automation opportunities and translate domain knowledge into agentic AI systems.
- Drive adoption of agentic services by ensuring they are fast, reliable, and superior to manual alternatives.
Requirements
- BS/MS in Computer Science, Computer Engineering, or equivalent experience.
- 8+ years of software engineering experience, with at least 2 years in production LLM or agentic AI systems.
- Strong Python skills and experience with modern LLM frameworks (e.g., LangChain, LlamaIndex).
- Hands-on experience with RAG pipelines, tool-use/function-calling, multi-step agentic services, and scalable engineering.
- Proven experience delivering and refining agentic AI systems in a production environment.
- Solid software engineering fundamentals including system build, testing, observability, and scalable architecture.
- Strong analytical skills for reasoning about evaluation metrics like precision, recall, and false positive rates.
Benefits
- Equity
- Benefits