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 building automation that protects availability.
We are looking for a hands-on Principal Software Engineer to design, build, and operate these services. Your work will help OCI bring new AI network capacity online efficiently and keep that infrastructure running reliably.
This is an individual contributor role with ownership of significant features and service components. You will contribute to architectural decisions, lead projects from design through production, and mentor engineers through collaborative development.
Internal Responsibilities
What makes this work interesting:
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. Solve concurrency, consistency, scheduling, and failure recovery problems where correctness affects network availability.
Ownership from design to production. See your work through implementation and rollout, and use production feedback to improve it.
What you will do:
Design, implement, and operate distributed services supporting network modeling, configuration, and lifecycle operations across OCI’s AI and cloud infrastructure.
Extend network models, APIs, and automation to support expanding GPU infrastructure and new network architectures.
Build reliable workflows for concurrent and long-running changes, including state management, retries, recovery, and rollback.
Develop validation, testing, observability, and rollout mechanisms that make network changes safer.
Diagnose and resolve bottlenecks in service performance, data access, and change execution.
Partner with network engineering, infrastructure delivery, operations, and adjacent software teams to deliver capabilities across service boundaries.
Independently lead substantial projects from requirements and technical design through implementation, deployment, and production support.
Participate in operational support and incident investigations, turning findings into improvements that reduce recurring failures and manual work.
Mentor engineers through code reviews, design discussions, and collaborative problem solving.
What you bring:
7–10 years of software engineering experience, including experience designing, building, and operating distributed systems.
Strong programming skills and a record of delivering reliable production software.
Solid understanding of concurrency, consistency, fault tolerance, API design, and persistent state.
Experience owning significant features or service components throughout the software development lifecycle.
Ability to evaluate design tradeoffs, troubleshoot complex issues, and communicate technical decisions clearly.
Experience collaborating across teams and delivering projects with dependencies.
Sound judgment about testing, reliability, operational readiness, and safe infrastructure changes.
Experience that would help you succeed:
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.
You do not need prior experience with every technology in our environment. We value strong systems fundamentals, sound engineering judgment, and the ability to learn a complex domain.
External Responsibilities
What makes this work interesting:
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. Solve concurrency, consistency, scheduling, and failure recovery problems where correctness affects network availability.
Ownership from design to production. See your work through implementation and rollout, and use production feedback to improve it.
What you will do:
Design, implement, and operate distributed services supporting network modeling, configuration, and lifecycle operations across OCI’s AI and cloud infrastructure.
Extend network models, APIs, and automation to support expanding GPU infrastructure and new network architectures.
Build reliable workflows for concurrent and long-running changes, including state management, retries, recovery, and rollback.
Develop validation, testing, observability, and rollout mechanisms that make network changes safer.
Diagnose and resolve bottlenecks in service performance, data access, and change execution.
Partner with network engineering, infrastructure delivery, operations, and adjacent software teams to deliver capabilities across service boundaries.
Independently lead substantial projects from requirements and technical design through implementation, deployment, and production support.
Participate in operational support and incident investigations, turning findings into improvements that reduce recurring failures and manual work.
Mentor engineers through code reviews, design discussions, and collaborative problem solving.
What you bring:
7–10 years of software engineering experience, including experience designing, building, and operating distributed systems.
Strong programming skills and a record of delivering reliable production software.
Solid understanding of concurrency, consistency, fault tolerance, API design, and persistent state.
Experience owning significant features or service components throughout the software development lifecycle.
Ability to evaluate design tradeoffs, troubleshoot complex issues, and communicate technical decisions clearly.
Experience collaborating across teams and delivering projects with dependencies.
Sound judgment about testing, reliability, operational readiness, and safe infrastructure changes.
Experience that would help you succeed:
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.
You do not need prior experience with every technology in our environment. We value strong systems fundamentals, sound engineering judgment, and the ability to learn a complex domain.
