Senior System Software Engineer, Agentic Kernel Development

Nvidia

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Santa Clara, CA
Salary
$184,000–$287,500 / yr
Posted
3 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $204k
This role $236k
$154k most similar roles pay here $302k

This role pays more than 79% of similar roles. Most pay $171,950–$235,750 — the shaded band above. At the midpoint, this role pays about $236k versus about $204k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 899 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 886 roles with salary data.

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At a glance

TL;DR · Senior System Software Engineer, Agentic Kernel Development

As a Senior System Software Engineer, Agentic Kernel Development, you will join the GPU SW Kernel organization to build and productize agentic AI systems that operate directly on GPU software artifacts like source code, crash dumps, and CI/CD signals. You will manage the full lifecycle of these services, from prototyping through deployment, while building LLM-powered pipelines for automated bug triage, regression detection, and intelligent test coverage analysis. The role involves developing an agentic knowledge layer using MCP-based infrastructure to integrate with internal systems like Gerrit and Perforce. You will utilize Python, LangChain, LlamaIndex, and RAG pipelines to create multi-step agentic services. Your work focuses on solving technical challenges in GPU software development by creating reliable automation tools that improve release quality through advanced code generation and evaluation metrics for LLM outputs.

What you'll do

  • Build and productize agentic AI systems that operate directly on GPU software artifacts like source code and crash dumps.
  • Manage the full lifecycle of agentic services from initial prototype through evaluation and deployment.
  • Develop LLM-powered pipelines for automated bug triage, code generation, and regression detection.
  • Create an agentic knowledge layer and MCP-based infrastructure to integrate with internal developer tools.
  • Establish metrics and evaluation frameworks to measure precision and recall tradeoffs for AI outputs.
  • Identify high-impact automation opportunities by translating GPU software domain knowledge into technical requirements.
  • Deliver reliable, production-ready agentic services that replace manual workflows across GPU software teams.

What we're looking for

  • BS/MS in Computer Science, Computer Engineering, or equivalent experience.
  • 8+ years of software engineering experience.
  • Minimum of 2 years developing production LLM or agentic AI systems.
  • Strong Python skills and experience with modern LLM frameworks like LangChain or LlamaIndex.
  • Hands-on experience with RAG pipelines, tool-use/function-calling patterns, and multi-step agentic services.
  • Solid software engineering fundamentals including system build, testing, observability, and scalable architecture.
  • Strong analytical skills to evaluate precision/recall tradeoffs and metrics for agent outputs.
  • Experience building code agents or familiarity with GPU, driver, or systems software (preferred).

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