Forward Deployed Architect

NVIDIA is looking for a Forward Deployed Architect to provide technical leadership and strategic guidance across AI Accelerator engagements.

Job Summary As a Forward Deployed Architect, you will advise on architecture and integration, define what good looks like, and bring learnings back to inform the DSX product roadmap. You will work alongside customers and partners on infrastructure problems no one has solved yet, helping teams adopt NVIDIA technology the right way and shaping how new AI workloads get deployed.

Responsibilities

• Cross-Account Technical Leadership: Provide architectural direction across strategic engagements where standard capabilities are not enough and advanced implementation, optimization, or integration customization is needed.
• Outcome-Focused Implementation: Help customers integrate the right components to deliver on their outcomes.
• Hands-On Technical Leadership: Dive into complex technical challenges hands-on when needed to solve critical problems, validate architectures, or prove out solutions.
• Strategic Initiative Ownership: Lead technically demanding programs end to end, including third-party performance benchmarking across hardware and workloads.
• Pattern Identification and Knowledge Sharing: Identify common challenges and solution patterns across engagements.
• Technical Standardization: Develop standardized approaches, reference architectures, and structured guidance rooted in patterns from successful engagements.
• Cross-Functional Collaboration: Partner with product, engineering, and other customer-facing NVIDIA teams.
• Strategic Architecture: Design technical strategies for advanced AI workloads.
• New Hardware Enablement: Help develop new infrastructure patterns and playbooks for the latest NVIDIA hardware.

Requirements

• Bachelors degree or equivalent experience.
• 10+ years in technical roles such as solutions architecture, ML engineering, technical product management, or technical consulting.
• Strong technical leadership with the ability to guide teams and influence technical decisions without direct authority.
• Systems thinking with the ability to understand customer outcomes and translate them into clear technical requirements and architectures.
• Willingness to prototype, implement, validate, and troubleshoot hands-on when needed.
• A solid technical foundation in the technologies AI infrastructure is built on, especially Linux systems administration.

Nice to Have

• Solutions architecture or technical consulting background across multiple customer engagements simultaneously.
• A foundational cloud or distributed systems background built at hyperscaler scale.
• A public technical voice: blog posts, talks, open-source contributions, or reference work that shows depth and opinion.
• Hands-On Technical Expertise in one or more of: NVIDIA Stack, Inference Systems, Training Systems, Infrastructure, and Observability and Automation.