Senior Software Engineer, Agentic Engineering

Nvidia

Remote

Quick summary

Work type
Remote
Location
Santa Clara, CA
Salary
$184,000–$287,500 / yr
Posted
3 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $196k
This role $236k
$132k most similar roles pay here $304k

This role pays more than 85% of similar roles. Most pay $163,165–$228,612 — the shaded band above. At the midpoint, this role pays about $236k versus about $196k 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 928 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 916 roles with salary data.

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View all roles at Nvidia

At a glance

TL;DR · Senior Software Engineer, Agentic Engineering

As a Senior Applied Machine Learning Engineer on NVIDIA’s Agentic Engineering team within the Deep Learning Framework Group, you will work closely with early-adopter engineering teams to identify pain points and develop agentic workflows that automate code generation, testing, and tuning. Your day-to-day involves iterating with these teams to validate or revise plans based on evolving requirements, using Python and other tools to build scalable infrastructure for autonomous agents that optimize high-dimensional parameters in real hardware environments. Familiarity with multi-agent orchestration frameworks like LangChain/LangGraph is essential, as you will integrate these systems into git-native workflows and CI pipelines. This role requires a strong background in AI systems, experience with GPUs, and the ability to thrive in an ambiguous, self-directed environment while contributing to cross-organizational collaboration on agentic methodologies.

What you'll do

  • Develop deep understanding of early-adopter engineering teams' needs and identify areas for agentic workflow improvements.
  • Use technical judgment to distinguish durable architectural opportunities from fleeting trends in applied ML projects.
  • Agentify compiler infrastructure to enable autonomous high-dimensional optimizations with closed-loop validation on real hardware.
  • Build multi-agent orchestration systems using frameworks like LangChain/LangGraph, driving autonomous loops for continuous improvement.
  • Integrate agentic workflows into git-native development processes and CI pipelines for seamless testing and iteration.

What we're looking for

  • MS in Computer Science, Engineering, or equivalent 6+ years experience.
  • Strong Python development skills and working knowledge of GPUs.
  • Demonstrated projects using AI systems and shipping complex projects independently.
  • Experience building tools through direct partnership with internal customer teams.
  • Knowledge in multi-agent orchestration frameworks or LLM-based workflow automation.
  • Ability to lead technical work through changing requirements and evidence-driven revisions.

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