Senior Product Architect, K8s-Based AI Infrastructure
$184k - $357k • US, CA, Santa Clara • Full-time
Posted 1d ago
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Infrastructure Engineer
About the job
NVIDIA is seeking a visionary Product Architect with strong expertise in systems architecture to join our AI Infrastructure and Agentic AI team. You will design and shape the architectures that connect the world's most powerful AI clusters, transforming ideas into well-defined, functional products by balancing technical feasibility with user needs and market demands. This role is at the nexus of designing and overseeing cutting-edge AI solutions from conception through their entire lifecycle, focusing on efficiency and multiplying efforts.
Responsibilities
- Propose new product concepts by staying at the forefront of technology trends in AI Infrastructure & Agentic AI.
- Define detailed product architectures, including performance, scalability, interoperability, and datacenter deployment requirements.
- Lead prototyping and testing processes to validate product design and functionality, focusing on scale, diagnosing bottlenecks, and driving performance innovations.
- Iterate and refine designs based on feedback, testing results, and evolving requirements.
- Collaborate with internal hardware, software, security, and systems teams to ensure flawless integration of networking, compute, and storage ecosystems.
- Conceptualize ideal solutions with partners and customers, building proof-of-concepts (POCs) and minimum viable products (MVPs).
- Provide comprehensive documentation for product designs, including technical specifications and user guides.
- Develop targeted content such as whitepapers, blogs, and curriculum for customers, partners, and users.
Requirements
- 8+ years of experience architecting datacenter-scale HPC or AI infrastructure as a Principal Architect, Solutions Architect, Principal Engineer, or equivalent.
- Bachelors degree in computer science or related field (or equivalent experience).
- Strong background in technologies enabling large-scale infrastructure management of complex systems, networks, and storage.
- Extensive experience with DevOps solutions, including Python, Ansible, Container Runtimes, and Kubernetes.
- Familiarity with AI workloads, including agentic & RAG-based workflows, inference at scale, large-scale training & fine-tuning, and model evaluation.
- Exceptional communication skills, with the ability to translate complex technical details for diverse audiences.
- Passion for staying updated with the latest technological advancements in AI and related fields.
Benefits
- Equity
- Benefits