NVIDIA is looking for Senior Cloud Infrastructure Solutions Architect with extensive DevOps platforms and Accelerated Compute Infrastructure experience to join its ANZ Team, specificically focused on working with our Neo Clouds. Enterprise, Academic Research groups around the world are using NVIDIA products to redefine deep learning and data analytics, and to power data workloads. Be involved with the crew developing many of the largest and fastest AI/HPC systems in the world! We are looking for someone with the ability to work on a dynamic customer focused team that requires excellent interpersonal skills. This role will be interacting with Neo Clouds, customers, partners and various departments, to analyze, define and implement large scale AI Operational projects. The scope of these efforts includes a combination of System Building, Kubernetes-based platforms, Automation, Hardware and Networking.

What you'll be doing:

• Maintaining large scale computational and AI infrastructure, focusing on monitoring, logging, workload orchestration (Kubernetes and Linux job schedulers).
• Optimize scalable, production-ready Kubernetes-based container platforms coordinated with enterprise-grade networking and storage.
• Serve as a key technical resource, develop, refine, and document standard methodologies and operational guidelines to be shared with internal teams.

• Lead technical engagements, helping customers troubleshoot, resolve complex issues, and advocate for their technical needs.

• Support Enterprise, Research & Development activities and engage in POCs/POVs to validate new features, architectures, and upgrade approaches.

• Partner with APAC Regional and HQ Engineering, Product and Sales teams to develop, plan best suitable solutions for Partners. Enable development and growth of product features through customer feedback and proof-of-concept evaluations
• Develop tooling to automate deployment and management of large-scale infrastructure environments, to automate operational monitoring and alerting, and to enable self-service consumption of resources.

• Create and deliver high-quality documentation, including runbooks, onboarding materials, and best-practice guides for customers and internal teams.
• Become the technical leader for assigned customer accounts, providing strategic guidance on DevOps and platform architecture and influencing long-term infrastructure and operations decisions.

What we need to see:

• Education & Experience: BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields, with 5+ years of professional experience in managing scalable cloud environments and automation engineering roles.
• Proven Hardware & Software knowledge and experience at scale: Familiarity with HPC and AI technologies (CPUs, GPUs, high-speed interconnects) and supporting software stacks.
• Cloud & HPC Expertise: Proven understanding of networking fundamentals (TCP/IP stack), data center architectures (from storage to Network, GPU accelerated compute and of course DevOps software stacks, as well as hands-on experience managing HPC/AI clusters, including deployment, optimization, and fixing issues.
• Kubernetes & AI/ML Workloads: Extensive experience with Kubernetes for container orchestration, resource scheduling, scaling, and integration with HPC environments.
• Linux & Storage Systems: Deep knowledge of Linux (RedHat/CentOS, Ubuntu), OS-level security, and protocols (TCP, DHCP, DNS). Experience with storage solutions such as Lustre, GPFS, ZFS, XFS, and emerging Kubernetes storage technologies.
• Automation & Observability: Proficiency in Python and Bash scripting, configuration management, and Infrastructure-as-Code tools (e.g., Ansible, Terraform). Experience with observability stacks (Grafana, Loki, Prometheus) for monitoring, logging, and building fault-tolerant systems.
• Solution Architecture & Customer Engagement: Strong background in crafting scalable solutions and providing consultative support to customers.

Ways to stand out from the crowd:

• Experience with GPU-focused hardware and software (e.g., NVIDIA DGX, CUDA, GPU Operator).
• Solid hands-on knowledge of Kubernetes and container-based microservices architectures.

• Skills in large-scale computing and cluster computing, data center design include high speed interconnect with Spectrum/InfiniBand, Cluster Storage and Scheduling related design and/or management experience.
• Knowledge of CI/CD pipelines for software deployment and automation.

• Background with RDMA-based fabrics (InfiniBand or RoCE) in HPC or AI environments.

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 in the world working for us. If you're creative and autonomous, we want to hear from you!

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.