This role pays more than
80%
of similar roles. Most pay
$162,762–$226,350
— the shaded band above.
At the midpoint, this role pays about
$226k
versus about
$195k
for comparable roles.
Based on 240 similar postings.
Employer
About Oracle
Oracle Corporation is a leading multinational technology company specializing in database software, cloud computing, and enterprise software.
Oracle currently has
528 open roles
on FindRole.
Listed pay typically runs
$102,300–$209,500
across 416 roles with salary data.
As a Lead Principal Core Infrastructure Engineer, you will join the team as a key architect focused on solving complex infrastructure challenges across sites, campuses, and colocation facilities. You will be responsible for enabling high-density AI deployments by performing site selection, capacity planning, power and cooling design, connectivity planning, and multi-site readiness assessments. Your daily work involves evaluating data-hall constraints such as physical layout, rack placement, and density limits while developing flexible infrastructure options and late-binding strategies. You will utilize expertise in modern data center architecture, high-performance networking, scale-out connectivity, and storage-related network demand to support AI environments. The role requires coordinating across facilities, network, storage, hardware, and software teams to manage the technical requirements of accelerator platforms and large-scale cloud infrastructure deployment within a complex, evolving technological landscape.
Design infrastructure for high-density AI deployments across sites, campuses, and colocation facilities.
Perform site selection and evaluate data-hall constraints including layout, power availability, and cooling capacity.
Conduct capacity planning and rack-power modeling specifically for high-density AI infrastructure.
Design power, cooling, and networking systems to support high-performance computing environments.
Develop flexible infrastructure options and late-binding strategies to accommodate evolving technology and customer requirements.
Assess multi-site deployment readiness and manage platform or capacity pivots.
Communicate architectural decisions, deployment risks, and technical tradeoffs to executive stakeholders.
What we're looking for
Must have 10+ years of experience in the field.
Strong knowledge of modern data center and campus architecture including power, cooling, networking, storage connectivity, and physical infrastructure.
Experience developing AI infrastructure deployment strategies across sites, campuses, or colocation environments.
Ability to evaluate site and data-hall constraints such as layout, rack placement, power availability, and cooling capacity.
Experience with capacity planning and rack-power modeling for high-density AI infrastructure.
Strong understanding of high-performance networking, scale-out connectivity, and storage-related network demand for AI environments.
Ability to communicate architectural decisions, risks, and tradeoffs to technical and executive stakeholders.
8+ years of experience in data center architecture, infrastructure engineering, capacity planning, or large-scale cloud infrastructure deployment (preferred).
Data Center Architecture
AI Infrastructure
Capacity Planning
Power and Cooling Design
High-Performance Networking
Storage Connectivity
Colocation
HPC
Infrastructure Lifecycle Planning
Site Selection
Thermal Assessment
Rack-Power Modeling
Multi-site Deployment
Campus Planning
Java
Python
Distributed Systems
Microservices
CI/CD
DevOps
Data Modeling
Linux
Windows
Application Security
System Design
Software Architecture
Observability
Algorithms
Data Structures
Data Center Infrastructure
Thermal Management
Air Flow Design
Capacity Planning
Infrastructure Monitoring
Firmware
Site Documentation
RFI
RFP
RFQ
Electrical Engineering
C
C++
Rust
Linux
DPDK
SmartNICs
DPUs
Kernel Drivers
Packet Processing
SDN
Virtualization
Hardware-Software Co-design
Distributed Systems
Memory Management
Low-latency Systems
C++
Python
Java
Distributed Systems
SDN
L2/L3 Networking
Routing
Switching
Traffic Engineering
WAN
Machine Learning
AI
High Availability
Control Planes
Observability
SmartNICs