Lead Principal Software Engineer - Core Infrastructure

Lead Principal Software Engineer — AI Infrastructure, Network Modeling & Control

Build the network control software that enables OCI’s AI infrastructure to scale. Large-scale AI training and inference depend on reliable, high-performance networks connecting GPU infrastructure. Oracle Cloud Infrastructure’s Network Modeling and Control team builds the software that models these physical networks and enables their configuration, expansion, and safe operation.

Our services help turn infrastructure designs into working networks and coordinate changes as capacity grows. You will tackle distributed systems challenges at the intersection of software, networking, and AI infrastructure: maintaining consistent network state, coordinating concurrent changes, recovering from partial failures, and introducing automation that protects availability.

We are looking for a hands-on Lead Principal Software Engineer to shape the architecture and evolution of these services. Your decisions will help determine how efficiently OCI brings new AI network capacity online and how reliably that infrastructure operates.

This is an individual contributor role with technical influence across teams. You will define architecture, write and review critical code, lead complex initiatives through production, and mentor engineers.

Disclaimer:

Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements.

Range and benefit information provided in this posting are specific to the stated locations only

US: Hiring Range in USD from: $146,300 to $306,400 per annum. May be eligible for bonus, equity, and compensation deferral.


Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business.
Candidates are typically placed into the range based on the preceding factors as well as internal peer equity.

Oracle US offers a comprehensive benefits package which includes the following:
1. Medical, dental, and vision insurance, including expert medical opinion
2. Short term disability and long term disability
3. Life insurance and AD&D
4. Supplemental life insurance (Employee/Spouse/Child)
5. Health care and dependent care Flexible Spending Accounts
6. Pre-tax commuter and parking benefits
7. 401(k) Savings and Investment Plan with company match
8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for subsequent years of employment. Vacation accrual is prorated for employees working between 20 and 34 hours per week. Employees working fewer than 20 hours per week are not eligible for vacation.
9. 11 paid holidays
10. Paid sick leave: 72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours.
11. Paid parental leave
12. Adoption assistance
13. Employee Stock Purchase Plan
14. Financial planning and group legal
15. Voluntary benefits including auto, homeowner and pet insurance

The role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted.
As part of Oracle's onboarding process and consistent with applicable law, US-based employees are required to complete identity verification, which involves the collection and processing of their biometric information. Accommodations to this requirement may be granted following an individualized assessment.

• Direct impact on AI infrastructure. Build foundational software for the networks supporting GPU clusters and AI workloads.
• Software that controls physical systems. Translate network topology and intended configuration into safe, coordinated infrastructure changes.
• Challenging distributed systems problems. Address concurrency, consistency, scheduling, and failure recovery in services where correctness affects network availability.
• Architectural influence as infrastructure grows. Shape how our services accommodate larger networks, new topologies, and evolving AI infrastructure requirements.

• Lead architecture and hands-on development for distributed services supporting network modeling, configuration, and lifecycle operations across OCI’s AI and cloud infrastructure.
• Evolve network models, APIs, and automation to support expanding GPU infrastructure and new network architectures.
• Design reliable workflows for concurrent and long-running changes, with clear approaches to state management, retries, recovery, and rollback.
• Build safety into network automation through validation, controlled rollout, observability, and limits on the scope of failures.
• Improve service performance and scalability to accelerate infrastructure provisioning and network changes.
• Partner with network engineering, infrastructure delivery, operations, and adjacent software teams to bring new capabilities into production.
• Own major technical initiatives from problem definition through implementation, rollout, and measurable production outcomes.
• Mentor engineers and use production experience to improve architecture, reduce recurring failures, and eliminate manual work.

• 10+ years of software engineering experience, including substantial experience designing and operating distributed systems.
• Strong programming skills and a record of delivering complex production software.
• Deep understanding of concurrency, consistency, fault tolerance, API design, and persistent state.
• Experience making architectural decisions across services and explaining their tradeoffs clearly.
• Evidence of leading complex initiatives across teams while remaining close to implementation.
• Strong judgment about reliability, operational readiness, and safe infrastructure changes.

• Infrastructure software supporting AI/ML platforms, GPU clusters, or large-scale compute environments.
• Network automation, network modeling, configuration management, or infrastructure control systems.
• Workflow orchestration, reconciliation, or scheduling across distributed resources.
• Model-based testing, formal methods, or other techniques for verifying complex state transitions.