Senior Engineer, Agentic AI Workflows & GPU Systems

NVIDIA; United States; On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Job summary

NVIDIA's Agentic Engineering team in the Deep Learning Frameworks Group is building agentic workflows that automate code generation, testing, and tuning across NVIDIA's software stack. You will work with early-adopter teams to iteratively validate architectural opportunities and drive durable solutions for production GPUs.

The role emphasizes deep ML expertise, strong Python skills, and experience with LLM-based automation, compiler-related work, and hardware-aware optimization.

Qualifications

• MS in Computer Science, Engineering, or equivalent experience.
• 6+ years of experience in applicable fields.
• Strong Python development skills.
• Working knowledge of GPUs or other highly data-parallel systems.
• Demonstrated projects using and supporting AI systems.
• Track record of shipping complex projects with minimal direction.
• Experience building tools or systems with internal customer input.
• Ability to lead technical work through changing requirements.

Responsibilities

• Develop agentic workflows that automate code generation, testing, and tuning across NVIDIA's frameworks and tooling.
• Collaborate with internal teams to translate requirements into durable infrastructure.
• Lead multi-agent orchestration across frameworks and GPUs with proof points and iterations.
• Translate evidence into path forward, balancing innovation with reliability.

Skills

Python

GPU programming

Multi-agent orchestration

LLM-based workflow automation

Strong communication

Technical leadership

Education

MS in Computer Science or Engineering

Tools

LangChain

LangGraph

Git

CI pipelines

Job description

NVIDIA's Agentic Engineering team in the Deep Learning Frameworks Group is building agentic workflows that automate code generation, testing, and tuning across NVIDIA's software stack. You will work with early-adopter teams to iteratively validate architectural opportunities and drive durable solutions for production GPUs.

The role emphasizes deep ML expertise, strong Python skills, and experience with LLM-based automation, compiler-related work, and hardware-aware optimization.