Senior AI Engineer

NVIDIA; Santa Clara (CA); On-site; USD 224,000 - 357,000; Full time

Benefits offered by this job

Equity and benefits

Job summary

NVIDIA in Santa Clara, CA, seeks a Senior AI Engineer to evaluate AI tools and agentic workflows within NVIDIA software engineering. You will design and validate reference workflows for coding, testing, and troubleshooting, and surface AI-first recommendations across teams.

The role focuses on reducing turnaround time through massively parallel systems, optimizing performance and cost, and providing practical guidance on tool adoption, data management, and deployment in enterprise environments.

Qualifications

• MS in EE/CS or equivalent experience.
• 12+ years of work experience.
• Deep knowledge of LLMs, ML, and agentic AI and how context and tools affect task outcomes.
• Hands-on experience evaluating AI tools in software engineering workflows.

Responsibilities

• Evaluate AI tools, agent harnesses, and models on NVIDIA software workflows.
• Compare task success, output quality, reliability, latency, cost, and readiness.
• Design and validate reference workflows for coding, testing, and debugging.
• Identify where AI is best and surface gaps with AI-first recommendations.
• Provide guidance, configurations, and onboarding materials; train teams.

Skills

Python

Java

Go

Scripting & Automation

CI/CD tooling

Distributed systems

REST APIs

LLMs / ML / Agentic AI

Education

MS in EE/CS

Tools

Codex

Claude

Cursor

Greptile

CodeRabbit

Jenkins

Gitlab CI

Packer

Terraform

Artifactory

Ansible

Chef

Job description

Senior AI Engineer (AI evaluation and agentic workflows) role at NVIDIA in Santa Clara, CA (onsite).

Responsibilities

• Evaluate emerging and established AI tools, agent harnesses, and models on representative NVIDIA software engineering workflows
• Compare task success, output quality, reliability, latency, cost, and enterprise readiness
• Identify where AI is the best tool; surface gaps and recommend AI-first approaches based on hands-on evaluation of modern AI-native tools
• Design, implement, and validate reference workflows for coding, testing, code review, and troubleshooting using tools such as Codex, Claude, Cursor, Greptile, and CodeRabbit
• Introduce technologies that enable massively parallel systems to improve turnaround time by an order of magnitude
• Optimize performance and cost by locating bottlenecks across training, evaluation, and testing; improve throughput, latency, and efficiency
• Partner with AI product vendors to gather deep industry insights and share findings with leaders and developers internally
• Work with core and emerging tool vendors to evaluate new capabilities, influence product roadmaps, resolve adoption issues, and add useful features into NVIDIA’s AI ecosystem
• Provide AI tool and model selection guidance, recommended configurations, workflow examples, onboarding materials, and hands-on training

Requirements

• MS in EE/CS or equivalent experience
• 12+ years of work experience
• Strong understanding of LLMs, machine learning, and agentic AI, including how models, agent harnesses, context, and tool use affect end-to-end task outcomes
• Hands-on experience evaluating AI tools or models and applying LLMs to software engineering workflows, including:
  • experiment design
  • benchmark development
  • reproducibility
  • failure analysis
• Strong software engineering skills in Python; experience with Java or Go and extensive scripting and automation experience
• Experience building evaluation pipelines, developer tooling, or full-stack applications, including:
  • API integration
  • data management
  • deployment in cloud or enterprise environments
• Experience with CI/CD tooling such as Jenkins, Gitlab CI, Packer, Terraform, Artifactory, Ansible, Chef or similar tools
• Good understanding of distributed systems, including microservice architecture and REST APIs
• Familiarity with software development, testing, code review, and build workflows; ability to translate evaluation results into clear technical recommendations and practical guidance
• Ability to work across organizational boundaries to improve alignment and productivity between teams

Technologies

• AI
• Large language models (LLMs)
• Machine learning
• Agentic AI
• Codex
• Claude
• Cursor
• Greptile
• CodeRabbit
• Python
• Java
• Go
• Jenkins
• Gitlab CI
• Packer
• Terraform
• Artifactory
• Ansible
• Chef
• CI/CD
• Microservice architecture
• REST APIs
• Cloud
• API integration

Benefits

• Eligible for equity and benefits

Ways to stand out from the crowd

• Industry thought leader in AI, influenced AI ecosystem to deliver forward-looking solutions
• Expertise in agent harnesses, tool calling, MCP, retrieval-augmented generation (RAG), context management, or fine-tuning, and experience evaluating their impact on complex engineering workflows
• Experience rolling out AI tools across engineering teams, collaborating with vendors, and turning emerging capabilities into measurable adoption and productivity improvements
• Experience developing large-scale distributed tooling, evaluation services, or observability systems with real-time constraints
• Strong collaborative and interpersonal skills, with a record of guiding and influencing others in dynamic environments

Compensation: USD 224,000 - 356,500 per year.

Location: Santa Clara, CA (onsite).