Senior Software Engineer, Agentic Engineering

Nvidia

Remote

Quick summary

Work type
Remote
Location
Santa Clara, CA
Salary
$184,000–$287,500 / yr
Posted
9 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $184k
This role $236k
$128k most similar roles pay here $305k

This role pays more than 84% of similar roles. Most pay $145,000–$222,000 — the shaded band above. At the midpoint, this role pays about $236k versus about $184k 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 980 open roles on FindRole.

Listed pay typically runs $168,000–$270,250 across 966 roles with salary data.

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View all roles at Nvidia

At a glance

TL;DR · Senior Software Engineer, Agentic Engineering

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As a Senior Applied Machine Learning Engineer on NVIDIA’s Agentic Engineering team within the Deep Learning Framework Group, you will collaborate closely with early-adopter engineering teams to identify pain points and develop agentic workflows that automate code generation, testing, and tuning across various frameworks and tools. Your day-to-day involves iterating on complex requirements, validating proof points, and building scalable infrastructure using modern AI techniques. Key responsibilities include agentifying compiler infrastructure for autonomous optimizations, orchestrating multi-agent systems with frameworks like LangChain/LangGraph, and integrating these workflows into git-native CI pipelines. The role requires strong Python skills, experience with GPUs, and a track record of shipping complex projects independently while adapting to changing requirements. Familiarity with NVIDIA’s latest hardware and emerging ML techniques is essential, as you will contribute to the broader organization's adoption of agentic methodologies.

Skills

Python LangChain LangGraph Kubernetes Docker CI/CD Git LLM-based workflow automation Compiler infrastructure Intermediate representations Program transformation Autonomous search High-dimensional optimization Hardware-aware performance optimization Deep learning workloads Code generation systems Domain-specific languages GPU programming Emerging kernel programming techniques Evaluation harnesses Testing frameworks

What you'll do

  • Develop deep understanding of NVIDIA's early-adopter engineering teams' needs.
  • Identify high-impact areas for agentic workflows within complex systems.
  • Use technical judgment to distinguish durable architectural opportunities from hype.
  • Agentify compiler infrastructure for autonomous high-dimensional optimizations.
  • Integrate agentic systems into git-native workflows and CI pipelines.
  • Contribute to cross-organizational sharing of reusable agentic methodology.

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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