Senior Forward Deployed Architect, Generative AI

About the role

NVIDIA is looking for a Senior Forward Deployed Architect to provide technical leadership and strategic guidance across AI accelerator engagements with AI native organizations, NeoCloud providers and ISVs. The role advises on architecture and integration, defines what good looks like and brings learnings back to inform the DSX product roadmap. It is engaged when standard product capabilities are not enough and the work needs to be specialized.

Key responsibilities

• Provide cross-account architectural direction for engagements needing advanced implementation, optimization or integration customization.
• Help customers integrate the right components to deliver outcomes, advising on DSX software adoption or alternatives, and feed gaps back to product and engineering.
• Dive into complex technical challenges hands-on to solve critical problems, validate architectures and prove out solutions.
• Lead technically demanding programs end to end, including third-party performance benchmarking across hardware and workloads.
• Identify common challenges and solution patterns, share findings internally and with the broader AI community, and develop standardized approaches and reference architectures.
• Design technical strategies for advanced AI workloads (distributed training, large-scale inference, model and pipeline optimization, MLOps) and help develop infrastructure patterns and playbooks for new NVIDIA hardware.

Required profile

• Bachelor's degree or equivalent experience.
• 10+ years in technical roles such as solutions architecture, ML engineering, technical product management or technical consulting, or alternatively 5+ years of specialist-level experience at the frontier of AI infrastructure.
• Strong technical leadership, able to guide teams and influence technical decisions without direct authority.
• Systems thinking and willingness to prototype, implement, validate and troubleshoot hands-on.
• Self-directed learner and strong communication skills with technical teams, executives and cross-functional collaborators.

Required skills

• Solid technical foundation in AI infrastructure, especially Linux systems administration.
• Preferred: solutions architecture or technical consulting background, hyperscaler-scale cloud or distributed systems experience, and a public technical presence.
• Preferred expertise in the NVIDIA stack (CUDA, NeMo, Triton, TensorRT, NIM, DGX Cloud, DSX), inference and training systems, infrastructure (SLURM, Kubernetes, GPU scheduling) and observability and automation (CI/CD, infrastructure as code).