SVP, Compute

Role Overview

The Senior Vice President of Compute Platform will lead the next phase of evolution of the foundational compute platform that underpins the entire Compute and AI Infrastructure portfolio. This executive will be responsible for taking an already established compute platform to the next level of scale, consistency, efficiency, reliability, and architectural maturity. The role spans the hardware-software interface, standard compute control plane and data plane, host software, lifecycle management, and the core abstractions through which compute infrastructure is provisioned, operated, secured, and consumed. The SVP will drive greater standardization and simplification across the compute stack, strengthen common platform capabilities, improve hardware-software integration, and increase the speed and efficiency with which new compute technologies can be introduced into the fleet.

A critical part of this mandate will be leading the AI transformation of the compute platform and engineering organization. The SVP will identify and drive the use of AI across software development, operations, reliability engineering, fleet management, capacity optimization, incident response, engineering productivity, and decision-making to materially improve how the platform is built and operated. This role requires more than outstanding engineering leadership. The SVP must also operate as a strong business leader with a clear business-outcome mindset. They will connect technical and AI-driven transformation initiatives to customer impact, growth, cost, efficiency, reliability, margin, and capital productivity, while maintaining deep visibility into the business and operational metrics that define platform performance.

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Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans' status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.

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: $347,800 to $623,900 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.

Key Responsibilities

• Advance the End-to-End Compute Platform

• Own the architecture, strategy, roadmap, execution, and operational outcomes for the common compute platform underpinning the broader compute infrastructure portfolio.

• Evolve the platform toward greater consistency, modularity, scalability, reliability, and operational efficiency.

• Strengthen common platform capabilities, reduce fragmentation, and continuously improve the architecture to support increasing scale and complexity.

AI Transformation of the Platform

• Lead the transformation of the compute platform and engineering organization through the application of AI.

• Establish a clear strategy for applying AI across software engineering, platform operations, reliability, capacity management, fleet optimization, testing, observability, and incident management.

• Drive adoption of AI-assisted software development and AI-enabled operations to improve productivity, software quality, anomaly detection, root-cause analysis, automated remediation, capacity forecasting, and fleet optimization. Establish measurable goals for engineering productivity, incident reduction, operational efficiency, deployment velocity, utilization, and cost.

Hardware-Software Interface

• Strengthen the interface between hardware and software engineering to improve how new compute technologies are integrated, qualified, deployed, and operated.

• Drive consistent interfaces across firmware, operating systems, device drivers, accelerators, networking, storage, and platform-management components.

Compute Control Plane

• Own and continuously evolve the standard compute control plane across the compute portfolio. Improve the scale, reliability, efficiency, and consistency of capacity management, scheduling, placement, provisioning, configuration, orchestration, lifecycle management, health management, and fleet operations.

Compute Data Plane

• Own the evolution of the foundational compute data plane and host software architecture.

• Drive greater standardization across virtualization, bare metal, containers, accelerated computing, networking, storage integration, workload isolation, security enforcement, and runtime management.

Platform Architecture and Standardization

• Drive architectural simplification and standardization across the compute organization.

• Establish clear and stable contracts between platform layers and higher-level products, strengthen API consistency and backward compatibility, and use AI-assisted analysis and engineering tools to accelerate modernization.

Business Outcome and Operational Leadership

• Operate as both an engineering leader and a business leader for the compute platform.

• Ensure engineering and AI transformation priorities are directly connected to measurable business outcomes including customer experience, revenue growth, infrastructure efficiency, cost reduction, margin improvement, capacity availability, and capital productivity.

Reliability, Security, and Operational Excellence

• Raise the bar on availability, resiliency, security, performance, and operational efficiency.

• Apply AI to accelerate anomaly detection, root-cause analysis, incident response, predictive maintenance, and automated recovery.

AI and Accelerated Compute

• Evolve the compute platform to support the rapidly increasing scale and complexity of AI and accelerated infrastructure.

• Strengthen common platform capabilities for GPUs, custom accelerators, large-scale clusters, and emerging AI infrastructure architectures.

Engineering Leadership and Organization

• Lead a world-class engineering organization spanning compute platform architecture, systems software, control plane, host software, fleet management, virtualization, and infrastructure services.

• Build a culture of technical excellence, accountability, simplification, scalability, operational discipline, business ownership, and AI-enabled engineering.

Leadership Impact

• Greater consistency and standardization across the compute platform.

• A more scalable, reliable, and efficient compute control plane and data plane.

• Higher fleet reliability, utilization, automation, and operational efficiency.

• Material improvements in engineering productivity through AI-assisted development and operations.

• Greater use of predictive and autonomous capabilities across fleet operations.

• Improved infrastructure economics and capital efficiency.

• A compute platform capable of supporting the next generation of cloud and AI workloads at significantly greater scale.

Minimum Qualifications

• 15+ years of experience in large-scale infrastructure, distributed systems, cloud computing, systems software, or related engineering domains.

• Significant senior engineering leadership experience managing large, globally distributed engineering organizations.

• Deep understanding of compute infrastructure and distributed systems.

• Proven experience evolving and operating infrastructure platforms at hyperscale.

• Demonstrated success improving scalability, reliability, operational efficiency, and economics of mission-critical infrastructure.

• Strong track record of driving platform standardization and architectural simplification.

• Demonstrated ability to apply emerging technologies, including AI, to transform engineering productivity and operational effectiveness.

• Strong business and operational acumen, with experience using business, financial, and operational metrics to drive priorities and investments.

Preferred Qualifications

• Experience in a senior leadership role at a leading hyperscale cloud provider.

• Experience owning major portions of a cloud compute platform, host platform, virtualization stack, or infrastructure control plane.

• Deep familiarity with GPU and accelerated computing infrastructure.

• Experience operating infrastructure across hundreds of thousands or millions of servers.

• Experience driving AI-enabled transformation across large software or infrastructure engineering organizations.

• Strong understanding of cloud infrastructure economics, including utilization, cost of capacity, capital efficiency, and unit economics.

Executive Profile

This role requires a systems leader who can take a highly capable compute platform and elevate it to the next level of scale, simplicity, standardization, operational excellence, and business impact.The ideal leader combines deep technical credibility with strong business judgment and a forward-looking view of how AI can transform engineering and infrastructure operations. They will see AI not simply as a workload the platform must support, but as a fundamental tool for transforming how the platform itself is engineered, operated, optimized, and evolved.

Key Responsibilities

• Advance the End-to-End Compute Platform

• Own the architecture, strategy, roadmap, execution, and operational outcomes for the common compute platform underpinning the broader compute infrastructure portfolio.

• Evolve the platform toward greater consistency, modularity, scalability, reliability, and operational efficiency.

• Strengthen common platform capabilities, reduce fragmentation, and continuously improve the architecture to support increasing scale and complexity.

AI Transformation of the Platform

• Lead the transformation of the compute platform and engineering organization through the application of AI.

• Establish a clear strategy for applying AI across software engineering, platform operations, reliability, capacity management, fleet optimization, testing, observability, and incident management.

• Drive adoption of AI-assisted software development and AI-enabled operations to improve productivity, software quality, anomaly detection, root-cause analysis, automated remediation, capacity forecasting, and fleet optimization. Establish measurable goals for engineering productivity, incident reduction, operational efficiency, deployment velocity, utilization, and cost.

Hardware-Software Interface

• Strengthen the interface between hardware and software engineering to improve how new compute technologies are integrated, qualified, deployed, and operated.

• Drive consistent interfaces across firmware, operating systems, device drivers, accelerators, networking, storage, and platform-management components.

Compute Control Plane

• Own and continuously evolve the standard compute control plane across the compute portfolio. Improve the scale, reliability, efficiency, and consistency of capacity management, scheduling, placement, provisioning, configuration, orchestration, lifecycle management, health management, and fleet operations.

Compute Data Plane

• Own the evolution of the foundational compute data plane and host software architecture.

• Drive greater standardization across virtualization, bare metal, containers, accelerated computing, networking, storage integration, workload isolation, security enforcement, and runtime management.

Platform Architecture and Standardization

• Drive architectural simplification and standardization across the compute organization.

• Establish clear and stable contracts between platform layers and higher-level products, strengthen API consistency and backward compatibility, and use AI-assisted analysis and engineering tools to accelerate modernization.

Business Outcome and Operational Leadership

• Operate as both an engineering leader and a business leader for the compute platform.

• Ensure engineering and AI transformation priorities are directly connected to measurable business outcomes including customer experience, revenue growth, infrastructure efficiency, cost reduction, margin improvement, capacity availability, and capital productivity.

Reliability, Security, and Operational Excellence

• Raise the bar on availability, resiliency, security, performance, and operational efficiency.

• Apply AI to accelerate anomaly detection, root-cause analysis, incident response, predictive maintenance, and automated recovery.

AI and Accelerated Compute

• Evolve the compute platform to support the rapidly increasing scale and complexity of AI and accelerated infrastructure.

• Strengthen common platform capabilities for GPUs, custom accelerators, large-scale clusters, and emerging AI infrastructure architectures.

Engineering Leadership and Organization

• Lead a world-class engineering organization spanning compute platform architecture, systems software, control plane, host software, fleet management, virtualization, and infrastructure services.

• Build a culture of technical excellence, accountability, simplification, scalability, operational discipline, business ownership, and AI-enabled engineering.

Leadership Impact

• Greater consistency and standardization across the compute platform.

• A more scalable, reliable, and efficient compute control plane and data plane.

• Higher fleet reliability, utilization, automation, and operational efficiency.

• Material improvements in engineering productivity through AI-assisted development and operations.

• Greater use of predictive and autonomous capabilities across fleet operations.

• Improved infrastructure economics and capital efficiency.

• A compute platform capable of supporting the next generation of cloud and AI workloads at significantly greater scale.

Minimum Qualifications

• 15+ years of experience in large-scale infrastructure, distributed systems, cloud computing, systems software, or related engineering domains.

• Significant senior engineering leadership experience managing large, globally distributed engineering organizations.

• Deep understanding of compute infrastructure and distributed systems.

• Proven experience evolving and operating infrastructure platforms at hyperscale.

• Demonstrated success improving scalability, reliability, operational efficiency, and economics of mission-critical infrastructure.

• Strong track record of driving platform standardization and architectural simplification.

• Demonstrated ability to apply emerging technologies, including AI, to transform engineering productivity and operational effectiveness.

• Strong business and operational acumen, with experience using business, financial, and operational metrics to drive priorities and investments.

Preferred Qualifications

• Experience in a senior leadership role at a leading hyperscale cloud provider.

• Experience owning major portions of a cloud compute platform, host platform, virtualization stack, or infrastructure control plane.

• Deep familiarity with GPU and accelerated computing infrastructure.

• Experience operating infrastructure across hundreds of thousands or millions of servers.

• Experience driving AI-enabled transformation across large software or infrastructure engineering organizations.

• Strong understanding of cloud infrastructure economics, including utilization, cost of capacity, capital efficiency, and unit economics.

Executive Profile

This role requires a systems leader who can take a highly capable compute platform and elevate it to the next level of scale, simplicity, standardization, operational excellence, and business impact.The ideal leader combines deep technical credibility with strong business judgment and a forward-looking view of how AI can transform engineering and infrastructure operations. They will see AI not simply as a workload the platform must support, but as a fundamental tool for transforming how the platform itself is engineered, operated, optimized, and evolved.