Senior Software Engineer, AI Infrastructure Solutions

at Nvidia

USD 152,000-241,500 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 @ 6 Agentic AI CUDA @ 6 Communication @ 6 Data Pipelines @ 6 Debugging @ 7 GPU @ 6 LLM MLOps @ 4 Machine Learning Observability @ 4 Python @ 7 RAG Security

Details

NVIDIA's Modular Diagnostics team develops diagnostic applications and infrastructure to test NVIDIA GPUs and ensure performance before launch. This role focuses on building intelligent automation to accelerate GPU validation and improve engineering workflows.

Responsibilities

Build and deliver agentic AI solutions—autonomous systems that reason, plan, and take actions—to automate silicon bring-up, testing and validation frameworks, debugging, and engineering workflows.
Build scalable AI infrastructure, services, APIs, and reusable platforms for developing and deploying AI-powered applications across NVIDIA.
Integrate AI agents with engineering tools, knowledge bases, data platforms, and existing business processes to create end-to-end intelligent workflows.
Partner with multifunctional teams to identify high-impact use cases, define requirements, develop prototypes, and deploy production-ready solutions.
Establish evaluation, observability, security, and reliability practices for AI systems operating at scale and meeting enterprise standards.
Drive projects from concept through adoption, measure impact against clear success criteria, and continuously improve efficiency.

Requirements

BS or MS degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
5+ years of experience delivering production software, infrastructure, platform, or AI solutions.
Strong programming skills in Python and C/C++.
Experience building applications with large language models, AI agents, retrieval-augmented generation, tool use, or workflow orchestration.
Demonstrated ability to build scalable services, APIs, data pipelines, and production software infrastructure.
Strong problem-solving, debugging, and system-design skills, with a history of shipping reliable systems.
Effective collaboration across technical and business teams, with clear communication and the ability to drive solutions from idea to production.

Preferred Qualifications

Background in GPU computing, CUDA, GPU architecture, or silicon bring-up processes.
Familiarity with engineering diagnostics, hardware development workflows, or systems software.
Experience with MLOps, model evaluation frameworks, AI observability tools, or production AI monitoring.
Contributions to open-source AI/ML projects or developer tools.
Experience building internal developer platforms or engineering efficiency tooling.

Compensation and Benefits

The base salary range is USD 152,000–241,500, determined by location, experience, and the pay of employees in similar positions. The role is also eligible for equity and benefits.

Applications will be accepted at least until October 26, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is committed to an inclusive, equal-opportunity work environment.