Long applicationsign-up on Oracle

Lead Principal Core Infrastructure Engineer

Oracle • CRM Software • Cloud Platforms (IaaS & PaaS) • 21 days ago

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Salary

≈ $111k – $229k per year (Estimated)

Location

In office (Nashville)

Seniority

Principal

Visa

H-1B filings in 12 months: 1,038 · for this role: 747 · green card filings: 729

Confirmed on the employer's own hiring board on Oct 19, 2026. First seen by Alion on Sep 29, 2026. Oracle scores A on the Alion truth index.

Overview

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Profile match

Oracle

Oracle is an American enterprise technology company founded in 1977 by Larry Ellison, Bob Miner and Ed Oates, and headquartered in Austin, Texas. It built its business on the Oracle Database, still the reference relational engine for large transactional systems, and has expanded into a full applications suite covering finance, human resources, supply chain and customer experience through Fusion Cloud and NetSuite. Its fastest growing segment is Oracle Cloud Infrastructure, which the company has positioned aggressively for AI training and inference workloads through large multi-year capacity contracts.

oracle.com • HQ: Austin, United States • CRM Software • HR & Payroll Software • ERP & Business Management Software • Cloud Platforms (IaaS & PaaS) • Databases & DBMS • 5000+ employees • Est. 1977

Tech stack of Oracle

Backed by NEA, Bessemer Venture Partners, General Catalyst

Oracle Core Infrastructure Engineering is seeking a highly driven Lead Principal Engineer for Data Center Architecture to define and deliver next-generation AI data center and campus solutions for Oracle Cloud Infrastructure (OCI). This role is responsible for translating AI capacity requirements, customer commitments, and technology roadmaps into scalable, reliable, and operationally efficient infrastructure designs.

The Data Center Architect will develop site, campus, and colocation strategies that integrate power, cooling, networking, storage connectivity, physical layout, and operational readiness for high-density AI environments. The role requires evaluating data-hall constraints, rack-power envelopes, thermal limits, capacity availability, and deployment schedules to determine the most effective solution for each site.

A key part of the role is creating deployment optionality across evolving AI platforms and infrastructure requirements. You will define late-binding strategies

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