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Lead technical engagements with cloud partners to design, integrate, and deploy large-scale GPU AI/HPC infrastructure. Drive proof-of-concepts, production delivery, performance tuning, and adoption of deep learning frameworks, models, and NVIDIA software across the customer lifecycle, while collaborating cross-functionally and presenting technical content.

The Senior HPC Architect role involves deploying large-scale GPU compute clusters, optimizing system administration, and collaborating with researchers on HPC and AI solutions.

Design and implement high-performance, scalable storage systems and client libraries for AI workloads. Build data loading, checkpointing, caching, POSIX-style and object-store integrations, observability and telemetry, and validate performance with platform, SRE, and AI teams using modern engineering practices.

Translate cutting-edge agent research into secure, production-grade runtime systems: prototype, benchmark, reproduce methods, build agent harnesses and evaluation/red-team workflows, secure agent toolchains, and partner across research, product, and engineering to integrate features into OpenShell.

As a Principal Software Engineer, you'll develop software systems for NVIDIA's rack-scale infrastructure, defining software architecture, collaborating across teams, mentoring engineers, and ensuring high-quality technical decisions in complex environments.

Build and maintain network automation and orchestration software for NVIDIA GPU Cloud and SuperPod deployments. Design/configure centralized configuration management, integrate cloud provider APIs, implement data pipelines and streaming telemetry, and automate lifecycle operations from procurement to deployment. Collaborate with infrastructure experts to deliver zero-touch, production-grade network provisioning, monitoring, and management tools.

Design, develop, and operate massively distributed GPU cluster platforms for DGX Cloud. Build tooling to identify, diagnose, and remediate non‑performant GPU assets; ensure reliable, high‑performance production AI clusters; collaborate across teams; evaluate failures and improve services; work across frontend and backend stack.

Design, integrate, and deploy large-scale AI/HPC GPU infrastructure with NVIDIA Cloud Partners. Drive technical engagements across the customer lifecycle, build PoCs, troubleshoot performance and scaling, and deliver technical content and workshops.

Serve as a trusted technical advisor to NVIDIA Cloud Partners to design, integrate, and deploy large-scale GPU AI/HPC cloud infrastructure. Lead PoCs and production deployments of models, frameworks, and software stacks, run technical workshops and presentations, collaborate with sales, engineering, and product teams, and drive customer adoption and consumption.

Lead engineers building and operating DGX Cloud infrastructure across NVIDIA Cloud Partner and on-prem environments. Drive cluster operations, Kubernetes operability, automation, GitOps, observability, and incident response. Define roadmap, staffing, and operational ownership while partnering with platform, storage, networking, security, and TPM teams. Mentor engineers and foster a healthy on-call and incident review culture focused on durable fixes and operational excellence.