Senior System Software Engineer, Agentic Kernel Development

NVIDIA; Santa Clara (CA); On-site; USD 184,000 - 357,000; Full time

Job summary

NVIDIA's GPU SW Kernel organization is seeking an experienced software engineer to build agentic AI systems that operate on GPU software artifacts, including source code, crash dumps, changelists, test results, and CI/CD signals. You will own the end-to-end lifecycle of agentic services from prototype to deployment and continuous improvement.

The role requires 8+ years in software engineering, strong Python, and hands-on experience with LLM frameworks and RAG pipelines.

Qualifications

• BS/MS in Computer Science, Computer Engineering, or equivalent experience.
• 8+ years of software engineering experience, including a minimum of 2 years developing production LLM or agentic AI systems.
• Strong Python skills and experience with modern LLM frameworks (LangChain, LlamaIndex, or equivalent).
• Hands-on experience with RAG pipelines, tool-use / function-calling patterns, multi-step agentic services, and timely engineering at scale.
• Solid software engineering fundamentals: system build, testing, observability, and scalable architecture.
• Strong analytical skills — comfortable reasoning about precision/recall tradeoffs, false positive rates, and evaluation methods for agent outputs.

Responsibilities

• Own the full lifecycle of agentic services: from prototype through evaluation, deployment, and continuous improvement
• Build robust LLM-powered pipelines for code generation, automated bug triage, regression detection, and intelligent test coverage analysis
• Develop the agentic knowledge layer and MCP-based infrastructure that allow agents to interact with internal developer systems (Gerrit, NVBugs, CI/CD, Perforce, Slack)
• Design and assess agent quality thoroughly — establish metrics, develop evaluations, measure precision/recall tradeoffs at each stage of the funnel
• Work closely with GPU SW kernel engineers to pinpoint high-impact automation opportunities and convert domain knowledge into effective agentic AI systems
• Drive adoption across GPU SW teams by shipping agentic services that are fast, reliable, and meaningfully better than the manual alternative!

Skills

Python

LLM frameworks

Agentic AI

RAG pipelines

Education

BS/MS in Computer Science or related field

Tools

LangChain

LlamaIndex

Gerrit

NVBugs

CI/CD

Perforce

Job description

Join NVIDIA's GPU SW Kernel organization, where we're groundbreaking the next generation of outstanding AI systems to transform GPU software development. Our team leads the effort in crafting agentic AI systems that improve the quality and efficiency of GPU software. This is an outstanding opportunity to grow innovative systems from promising projects to critically important infrastructure. Be part of a dynamic team that impacts GPU release quality and establishes new standards in AI-enhanced automation!

What You'll Be Doing

Compose, build, and productize agentic AI systems that operate directly on GPU software artifacts — source code, crash dumps, changelists, test results, and CI/CD signals.

• Own the full lifecycle of agentic services: from prototype through evaluation, deployment, and continuous improvement
• Build robust LLM-powered pipelines for code generation, automated bug triage, regression detection, and intelligent test coverage analysis
• Develop the agentic knowledge layer and MCP-based infrastructure that allow agents to interact with internal developer systems (Gerrit, NVBugs, CI/CD, Perforce, Slack)
• Design and assess agent quality thoroughly — establish metrics, develop evaluations, measure precision/recall tradeoffs at each stage of the funnel
• Work closely with GPU SW kernel engineers to pinpoint high-impact automation opportunities and convert domain knowledge into effective agentic AI systems
• Drive adoption across GPU SW teams by shipping agentic services that are fast, reliable, and meaningfully better than the manual alternative!

What We Need To See

• BS/MS in Computer Science, Computer Engineering, or equivalent experience
• 8+ years of software engineering experience, including a minimum of 2 years developing production LLM or agentic AI systems
• Strong Python skills and experience with modern LLM frameworks (LangChain, LlamaIndex, or equivalent)
• Hands-on experience with RAG pipelines, tool-use / function-calling patterns, multi-step agentic services, and timely engineering at scale
• Proven experience delivering and refining agentic AI systems within a live production settingSolid software engineering fundamentals: system build, testing, observability, and scalable architecture
• Strong analytical skills — comfortable reasoning about precision/recall tradeoffs, false positive rates, and evaluation methods for agent outputs

Ways To Stand Out From The Crowd

• Experience building code agents — automated generation, review, or repair of real codebases
• Background in GPU, driver, or systems software (even as a user or collaborator) and familiarity with CUDA, kernel-mode software, or GPU driver development workflows
• Experience with MCP servers, tool-calling agents, or multi-agent orchestration frameworks
• Contributions to open-source AI tooling, agentic frameworks, or developer efficiency tools
• Familiarity with CI/CD systems, crash analysis pipelines, or automated regression triage

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 18, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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