Business Development Manager, Global Public Sector

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Business Development Manager for NVIDIA's Global Public Sector, focusing on driving growth strategies for sovereign AI models and applications. This role involves enabling local AI model and application builders, leading country-level strategies, and promoting the NVIDIA AI stack across governments and public sector globally, with an emphasis on regulated industries.

What you'd actually do

  1. Drive sovereign AI ecosystem development across priority nations by enabling local AI model and application builders to adopt the NVIDIA AI stack
  2. Lead country-level strategies for sovereign AI, ensuring alignment with national data residency, security, and regulatory requirements while accelerating adoption of NVIDIA-powered training and inference pipelines.
  3. Work with a virtual team of technical, business, sales and marketing resources across NVIDIA and our business partners to drive mutual success.
  4. Promote end-to-end AI lifecycle capabilities (data curation, training, fine-tuning, inference, and deployment) with a strong emphasis on NVIDIA platforms such as NeMo/Nemotron, TensorRT, and DGX/Cloud infrastructure.
  5. Enable regulated industry adoption by translating compliance, governance, and privacy requirements into deployable NVIDIA-based AI architectures.

Skills

Required

  • 5+ years of business development experience in hi-tech selling technology solutions
  • Strong customer/partner relationship skills shown across multiple countries
  • Excellent written and oral communication skills in English
  • Understanding and expert delivery of key features, product messages, positioning

Nice to have

  • Master’s degree and/or MBA is desirable
  • Deep knowledge of NVIDIA AI stack (NeMo, Nemotron, CUDA, TensorRT, NIMs) across both training and inference stages.
  • Proven experience building or scaling national AI initiatives
  • Strong understanding of AI model lifecycle economics, including GPU utilization, training vs. inference cost tradeoffs, and optimization strategies.
  • Experience enabling local AI ecosystems (developers, startups, academia, public sector) with GenAI tooling and infrastructure.

What the JD emphasized

  • sovereign AI
  • regulated industry adoption
  • national data residency, security, and regulatory requirements