Compute Software Architect

Oracle Corporation; United States; On-site; USD 180,000 - 280,000; Full time

Job summary

Oracle Corporation is seeking an senior Software Architect for Compute Platform and Control Plane to shape the architecture of core cloud infrastructure. The role spans provisioning, scheduling, lifecycle management, fleet orchestration, and regional isolation, guiding the platform toward hyperscale reliability and engineering velocity.

The ideal candidate brings deep expertise in distributed systems, cloud-scale design, and architectural leadership, collaborating with engineers, product teams,

Qualifications

• 12+ years of experience in software engineering, distributed systems, cloud infrastructure, or large-scale platform development.
• Deep expertise in software architecture and distributed systems.
• Strong experience designing and operating large-scale, highly available services.
• Significant experience with cloud infrastructure or large-scale infrastructure platforms.
• Strong understanding of control-plane architecture, service APIs, state management, orchestration, and automation.
• Experience designing systems for scalability, reliability, fault tolerance, and operational efficiency.
• Ability to reason across large and complex software systems and identify architectural simplifications.
• Proven ability to influence technical direction across multiple engineering teams and organizations.
• Strong programming and systems fundamentals.

Responsibilities

• Define and evolve the architecture of the core compute software platform.
• Establish clear architectural principles, service boundaries, APIs, interfaces, and ownership models across compute platform components.
• Provide deep technical leadership across compute provisioning, scheduling and placement, capacity discovery and allocation, instance and host lifecycle management, configuration and state management, fleet orchestration, health monitoring and remediation, failure recovery, service APIs, and regional isolation.
• Lead architectural reviews and drive alignment on critical technical decisions across related engineering groups.

Skills

Software architecture

Distributed systems

Cloud infrastructure

Large-scale systems

Leadership

Programming fundamentals

Education

Bachelor's/Master's/PhD

Job description

Role Overview

The Software Architect, Compute Platform and Control Plane will be a senior individual contributor responsible for shaping the architecture and technical direction of the core software systems that power the Compute infrastructure platform. This role will work across the compute platform and control plane, spanning provisioning, scheduling, placement, lifecycle management, capacity orchestration, fleet management, service APIs, and the foundational distributed systems that support large-scale cloud infrastructure.The ideal candidate brings exceptional depth in software architecture, distributed systems, and cloud infrastructure, with the ability to reason across complex systems, identify structural weaknesses, simplify architectures, and define designs that can operate reliably at hyperscale.This architect will work closely with senior engineers, engineering leaders, product teams, and adjacent infrastructure organizations to evolve the compute platform to the next level of scalability, reliability, efficiency, and engineering velocity.

Internal Responsibilities

Key Responsibilities

Compute Platform Architecture

• Define and evolve the architecture of the core compute software platform.
• Establish clear architectural principles, service boundaries, APIs, interfaces, and ownership models across compute platform
  components.

Compute Control Plane Architecture

• Provide deep technical leadership across compute provisioning, scheduling and placement, capacity
  discovery and allocation, instance and host lifecycle management, configuration and state management,
  fleet orchestration, health monitoring and remediation, failure recovery, service APIs, and regional isolation.

Distributed Systems Leadership

• Serve as a technical authority for distributed systems design. Drive architectural rigor in consistency,
  concurrency, state management, partitioning, replication, idempotency, failure recovery, dependency
  management, and service isolation.

Cloud Infrastructure Architecture

• Apply deep cloud infrastructure expertise to the design and evolution of the compute platform. Understand
  the end-to-end lifecycle of cloud compute capacity, from resource discovery and orchestration through
  provisioning, customer consumption, maintenance, failure recovery, and retirement.

Reliability and Resiliency

• Embed reliability and resilience into the architecture of the platform. Design for fault containment, graceful
  degradation, recovery, retry safety, deployment safety, and failure isolation.
  Scalability and Performance
• Identify scaling limitations across the compute platform and control plane. Develop architectures that
  improve throughput, latency, efficiency, and resource consumption while reducing unnecessary
  infrastructure overhead.

Platform Simplification and Modernization

• Identify legacy complexity, duplicated services, and architectural patterns that limit engineering velocity or operational efficiency. Define pragmatic modernization strategies that allow critical systems to evolve without unnecessary disruption.

AI-Enabled Platform Transformation

• Help drive the use of AI to advance both the compute platform and software engineering practices. Identify opportunities to apply AI to software development, testing, code analysis, debugging, operational diagnostics, incident analysis, anomaly detection, failure prediction, root-cause analysis, capacity optimization, and automated remediation.

Technical Leadership and Influence

• Operate as a senior technical leader across organizational boundaries. Lead complex architecture reviews, drive alignment on critical technical decisions, mentor senior engineers, and partner with Distinguished Engineers, Architects, Directors, and Vice Presidents on long-term platform strategy.

Expected Impact

• A simpler, more coherent compute platform architecture.
• A highly scalable and resilient compute control plane.
• Clearer service boundaries and stronger platform APIs.
• Reduced architectural fragmentation and technical debt.
• Improved reliability and fault isolation.
• Better scalability and performance across critical services.
• Faster engineering velocity through reusable platform capabilities.
• More effective use of AI to improve engineering and operational workflows.

Minimum Qualifications

• 12+ years of experience in software engineering, distributed systems, cloud infrastructure, or large-scale platform development.
• Deep expertise in software architecture and distributed systems.
• Strong experience designing and operating large-scale, highly available services.
• Significant experience with cloud infrastructure or large-scale infrastructure platforms.
• Strong understanding of control‑plane architecture, service APIs, state management, orchestration, and automation.
• Experience designing systems for scalability, reliability, fault tolerance, and operational efficiency.
• Ability to reason across large and complex software systems and identify architectural simplifications.
• Proven ability to influence technical direction across multiple engineering teams and organizations.
• Strong programming and systems fundamentals.

Preferred Qualifications

• Experience designing cloud compute platforms or large-scale infrastructure control planes.
• Deep experience with scheduling, placement, provisioning, resource management, or fleet orchestration systems.
• Experience operating systems across multiple regions and failure domains.
• Experience modernizing large-scale infrastructure software while maintaining production stability.
• Strong understanding of cloud infrastructure economics and the relationship between architecture, utilization, and cost.
• Experience applying AI-assisted development or AI-driven operational techniques in production engineering environments.
• Experience working with GPU or accelerated compute infrastructure from a software platform perspective.
• Bachelor's, Master's, or PhD degree in Computer Science, Computer Engineering, or a related technical discipline.

Technical Profile

The ideal candidate is a hands‑on software architect with deep technical credibility and broad systems perspective. They are comfortable going deep into distributed protocols, state machines, consistency models, service interfaces, failure modes, and performance bottlenecks, while also reasoning about the architecture of a very large cloud platform as a whole.Most importantly, they will combine deep software architecture expertise with strong cloud infrastructure judgment and the ability to influence the direction of critical compute systems across the organization.

External Responsibilities

Key Responsibilities

Compute Platform Architecture

• Define and evolve the architecture of the core compute software platform.
• Establish clear architectural principles, service boundaries, APIs, interfaces, and ownership models across compute platform
  components.

Compute Control Plane Architecture

• Provide deep technical leadership across compute provisioning, scheduling and placement, capacity
  discovery and allocation, instance and host lifecycle management, configuration and state management,
  fleet orchestration, health monitoring and remediation, failure recovery, service APIs, and regional isolation.

Distributed Systems Leadership

• Serve as a technical authority for distributed systems design. Drive architectural rigor in consistency,
  concurrency, state management, partitioning, replication, idempotency, failure recovery, dependency management, and service isolation.

Cloud Infrastructure Architecture

• Apply deep cloud infrastructure expertise to the design and evolution of the compute platform. Understand the end-to-end lifecycle of cloud compute capacity, from resource discovery and orchestration through provisioning, customer consumption, maintenance, failure recovery, and retirement.

Reliability and Resiliency

• Embed reliability and resilience into the architecture of the platform. Design for fault containment, graceful degradation, recovery, retry safety, deployment safety, and failure isolation.
  Scalability and Performance
• Identify scaling limitations across the compute platform and control plane. Develop architectures that improve throughput, latency, efficiency, and resource consumption while reducing unnecessary infrastructure overhead.

Platform Simplification and Modernization

• Identify legacy complexity, duplicated services, and architectural patterns that limit engineering velocity or operational efficiency. Define pragmatic modernization strategies that allow critical systems to evolve without unnecessary disruption.

AI-Enabled Platform Transformation

• Help drive the use of AI to advance both the compute platform and software engineering practices. Identify opportunities to apply AI to software development, testing, code analysis, debugging, operational diagnostics, incident analysis, anomaly detection, failure prediction, root-cause analysis, capacity optimization, and automated remediation.

Technical Leadership and Influence

• Operate as a senior technical leader across organizational boundaries. Lead complex architecture reviews, drive alignment on critical technical decisions, mentor senior engineers, and partner with Distinguished Engineers, Architects, Directors, and Vice Presidents on long-term platform strategy.

Expected Impact

• A simpler, more coherent compute platform architecture.
• A highly scalable and resilient compute control plane.
• Clearer service boundaries and stronger platform APIs.
• Reduced architectural fragmentation and technical debt.
• Improved reliability and fault isolation.
• Better scalability and performance across critical services.
• Faster engineering velocity through reusable platform capabilities.
• More effective use of AI to improve engineering and operational workflows.

Minimum Qualifications

• 12+ years of experience in software engineering, distributed systems, cloud infrastructure, or large-scale platform development.
• Deep expertise in software architecture and distributed systems.
• Strong experience designing and operating large-scale, highly available services.
• Significant experience with cloud infrastructure or large-scale infrastructure platforms.
• Strong understanding of control‑plane architecture, service APIs, state management, orchestration, and automation.
• Experience designing systems for scalability, reliability, fault tolerance, and operational efficiency.
• Ability to reason across large and complex software systems and identify architectural simplifications.
• Proven ability to influence technical direction across multiple engineering teams and organizations.
• Strong programming and systems fundamentals.

Preferred Qualifications

• Experience designing cloud compute platforms or large-scale infrastructure control planes.
• Deep experience with scheduling, placement, provisioning, resource management, or fleet orchestration systems.
• Experience operating systems across multiple regions and failure domains.
• Experience modernizing large-scale infrastructure software while maintaining production stability.
• Strong understanding of cloud infrastructure economics and the relationship between architecture, utilization, and cost.
• Experience applying AI-assisted development or AI-driven operational techniques in production engineering environments.
• Experience working with GPU or accelerated compute infrastructure from a software platform perspective.
• Bachelor's, Master's, or PhD degree in Computer Science, Computer Engineering, or a related technical discipline.

Technical Profile

The ideal candidate is a hands‑on software architect with deep technical credibility and broad systems perspective. They are comfortable going deep into distributed protocols, state machines, consistency models, service interfaces, failure modes, and performance bottlenecks, while also reasoning about the architecture of a very large cloud platform as a whole.Most importantly, they will combine deep software architecture expertise with strong cloud infrastructure judgment and the ability to influence the direction of critical compute systems across the organization.