Build and scale faster on the purpose-built AI cloud, engineered from silicon to API. Backed by Accel.
About the role
As a Technical Due Diligence Manager, you'll evaluate the technical feasibility of AI infrastructure opportunities across the Americas before Nebius commits capital. Working within the Infrastructure Acquisition Group, you'll lead multidisciplinary engineering due diligence across powered land and build-to-suit developments, partnering with Site Selection, Engineering, Energy, Legal, and Project Development to identify technical risk, assess development feasibility, and support investment decisions.
What they're looking for
- Experience supporting hyperscale data center, AI infrastructure, or mission-critical developments
- Professional Engineer (PE), PMP, or similar technical certification
- Experience with large-scale infrastructure acquisition or development programs
- Knowledge of utility infrastructure, transmission, and power markets
More about this role
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage,...
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