Senior Applied AI Engineer

at Nvidia

USD 152,000-287,500 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 4 API @ 7 CI/CD @ 7 Claude Code @ 4 Codex @ 4 Communication @ 6 GitHub @ 4 LLM @ 4 Observability @ 7 Python @ 7 Security @ 7

Details

NVIDIA's applied AI team for chip design operates at the intersection of research, engineering, and product development, transforming research breakthroughs into real-world solutions. The role focuses on designing and scaling AI agents that can reason, plan, call tools, and write code, as well as building and maintaining the infrastructure required to deploy and run these agents in production.

Responsibilities

Design, develop, and improve scalable infrastructure for next-generation AI applications, including copilots and agentic tools.
Improve architecture, performance, and reliability to enable the use of LLMs and advanced agent frameworks at scale.
Collaborate with hardware, software, and research teams.
Mentor and support peers while promoting engineering best practices and technical excellence.
Stay current with advancements in AI infrastructure and contribute to continuous innovation.
Connect AI applications and agents with existing systems, services, databases, documentation, codebases, and enterprise workflows in a secure, reliable, and maintainable manner.

Requirements

A master's degree or higher, or equivalent experience, in Computer Science, Engineering, AI, or a related technical field.
At least 5 years of hands-on software engineering experience building production-grade software systems.
Demonstrated experience shipping AI- or LLM-powered applications, agents, or automation workflows into production environments.
Strong Python engineering skills, including the ability to design, prototype, and productionize AI-enabled services, APIs, integrations, automation workflows, and internal tools.
Practical experience building LLM-powered agents or agentic workflows, including hands-on use of Claude Code, OpenAI Codex, Cursor, GitHub Copilot, or equivalent coding agents.
Strong software engineering fundamentals and a production mindset, including system design, API design, testing, CI/CD, code quality, observability, security, databases, containers, and distributed or event-driven systems.
Ability to identify repetitive, high-friction, or knowledge-intensive workflows and turn them into practical AI-enabled tools, automations, or assistants.
End-to-end ownership of engineering solutions, from architecture and development through deployment, integration, and ongoing operations and support.
Excellent communication skills and a collaborative, proactive approach.
Experience with emerging integration patterns such as MCP or Skills is a plus.

Benefits

Equity and benefits.
NVIDIA is committed to an inclusive work environment and is an equal opportunity employer.

Compensation

The base salary depends on location, experience, and the pay of employees in similar positions. The stated base salary ranges are USD 152,000–241,500 for Level 3 and USD 184,000–287,500 for Level 4.