About the job
NVIDIA is seeking an AI Architect to join its AI Tools Team! This role will focus on the extensive scale-up of key AI solutions for NVIDIA's internal organization, working closely with various teams such as Graphics Processors, Mobile Processors, Deep Learning, Artificial Intelligence, and Driverless Cars to meet their infrastructure needs. The cloud services support nearly half a million automated jobs daily on five thousand servers, enhancing the productivity of thousands of NVIDIA software developers worldwide. The cloud hosts a diverse mix of machines and devices with various operating systems (Windows/Linux/Android) and hardware platforms, including NVIDIA GPUs and Tegra processors.
Responsibilities
Architect, build and enable internal AI platforms and solutions to be used by thousands of NVIDIANs worldwide.
Spot opportunities where AI is the best tool: uncover gaps, and recommend AI-first approaches over conventional solutions—grounded in hands-on evaluation of modern AI-native tools.
Set the north star with cross-functional teams: align on end-to-end AI system outcomes and translate them into clear, measurable objectives.
Introduce technologies enabling massively parallel systems to improve turnaround time by an order of magnitude.
Lead through influence: Drive, motivate, convince, and mentor sub-system owners to achieve improvements with agility, speed, and high engineering standards.
Optimize for performance and cost: identify bottlenecks across training, evaluation, and testing workflows and improve throughput, latency, and efficiency
Collaborate with AI product vendors to gain deep insights of the AI industry, and share them with leaders and developers internally.
Qualifications
Minimum
MS/PhD in AI/CS (or equivalent experience) with 12+ years building systems software, including 2+ years building/exploring AI solutions.
Hands-on experience with LLMs, RAG, fine-tuning, and agentic/workflow orchestration.
Strong “AI-first” approach and proficiency with modern AI-native developer ecosystems and tooling.
Validated experience deploying to hybrid, multi-cloud environments (and ideally edge).
Track record architecting and shipping large-scale distributed systems in production.
Proven ability to find system bottlenecks and deliver measurable performance/cost improvements.
Strong programming skills in Java and Python; validated understanding of distributed systems concepts and REST APIs.
Expertise with containerization and virtualization (Docker, VMs); Kubernetes experience is a plus.
Solid understanding of cloud/platform and data infrastructure tools such as OpenStack, Kubernetes, Chef/Puppet, Hadoop/Ceph/SwiftStack, LXC, Git/Perforce, JFrog, Kafka.
Excellent multi-functional influence skills—able to drive alignment across org boundaries in a global, multi-time-zone environment.
Preferred
Depth in AI, Machine Learning and Deep Learning algorithms and techniques.
Strong collaborative and interpersonal skills, with a proven record of guiding and influencing others in dynamic environments.
Industry thought leader in AI, influenced AI ecosystem to deliver forward looking solutions
Background in designing high-performance, scalable software systems with a strong focus on hardware cost optimization.