Equipment selection
Supported the selection of GPU cluster equipment for the data center deployment.
Applied AI · Earlier work
Enterprise AI Infrastructure Deployment Support
The unglamorous side of AI infrastructure — equipment selection, rack layout, and getting every team reading from the same document.
Technical support for enterprise-scale AI infrastructure deployment — GPU cluster equipment selection, data center cabling and rack layout coordination, and cross-team technical documentation.
- GPU Infrastructure
- Technical Proposals
- Vendor Coordination
Overview
This work involved providing technical support for the deployment of enterprise-scale AI infrastructure, centered on a GPU cluster data center build. It covered equipment selection, coordinating cabling and rack layout, and producing technical documentation to align the teams involved.
- Role
- Provided technical support across equipment selection, cabling/rack layout coordination, and cross-team technical documentation for the deployment.
Highlights
- Supported equipment selection for a GPU cluster data center deployment
- Coordinated cabling and rack layout planning
- Produced cross-team technical documentation to align stakeholders
Features
Cabling & rack layout
Coordinated cabling and rack layout planning for the physical data center build.
Technical documentation
Produced documentation to keep cross-functional teams aligned on the deployment.
Process
- Supported evaluation and selection of GPU cluster equipment
- Coordinated cabling and rack layout planning with the deployment team
- Wrote technical documentation to align stakeholders across teams
Challenges
- Coordinating cabling and rack layout decisions across multiple teams
- Producing documentation clear enough to align technical and non-technical stakeholders
Recorded result
Contributed technical support to an enterprise-scale GPU cluster data center deployment, from equipment selection through cabling/rack layout coordination and documentation.
Reflection
This project gave me visibility into the physical infrastructure layer that AI systems actually run on — a useful counterweight to the software/agent side of the work.