We are looking for a Senior AI Infrastructure Engineer (AI Tooling) to design and build the backend systems and infrastructure powering our internal AI tools and intelligent agents. This is a hands-on software engineering role with a strong infrastructure focus, ideal for someone who thrives at the intersection of backend development, systems engineering, and applied AI.
You will contribute to building robust, scalable systems that support a wide range of applied AI initiatives. These may include integrating LLMs via APIs, supporting internal ML models, working with AI agent frameworks, building data pipelines, and developing tools to improve AI reliability, observability, and deployment workflows. This is not a research or model training role. It is a practical engineering position focused on enabling and scaling real-world AI applications through solid infrastructure and backend development.
What you’ll be doing:
Build AI-powered tools that enhance operational excellence by leveraging diverse operational data, supporting incident, change, and problem management workflows
Collaborate closely with Incident Commanders, incident response, and SRE teams to integrate AI-driven automation and analytics into operational workflows
Design, develop, and maintain backend systems and infrastructure using Go and Python to support internal AI tools and intelligent agents
Build and maintain data pipelines using PySpark and related tools to support AI and analytics workflows
Operate and scale infrastructure using Kubernetes, managing containerized AI services and automating pipeline deployments
Work with vector databases to enable semantic search and retrieval-augmented generation use cases
Integrate large language models, agent systems, and classical ML models into internal services and automation workflows
Improve observability, deployment automation, and system reliability for AI-driven services
What we need to see:
8+ years of software engineering experience, with deep expertise in backend systems and infrastructure.
Bachelor's degree or equivalent experience.
Strong proficiency in Python and Go, with a track record of delivering reliable, scalable software solutions
Experience designing scalable, maintainable backend systems and writing clear design documentation
Deep experience with Kubernetes and cloud-native infrastructure
Experience working with building, deploying, and maintaining ML models in production systems
Familiarity with AI agent frameworks or orchestration tools
Solid understanding of system observability, monitoring, and performance optimization
Strong collaboration and communication skills to work across remote teams
Ways to stand out from the crowd:
Proven experience delivering AI-driven features end-to-end, from infrastructure design to production deployment
Experience with Temporal, Argo, or other workflow engines for multi-step or async job orchestration. Familiarity with vector databases and their applications in AI and LLM-powered systems
Contributions to open-source projects related to AI infrastructure, backend development, or developer tooling
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you are creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
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What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
