Senior Principal Software Engineer, Core Infrastructure

Oracle; Seattle (WA); On-site; USD 180,000 - 260,000; Full time

Job summary

Oracle Cloud Infrastructure (OCI) seeks a Senior Principal Software Engineer to build a new DPU platform spanning networking and storage. You will own a major subsystem, define architectural boundaries, and align owners across teams, with a focus on high-performance storage and networking data paths.

You will shape foundational data-path decisions, manage budgets, and drive production readiness while mentoring engineers and guiding cross-domain collaboration to deliver robust, scalable

Qualifications

• 10+ years of professional software engineering experience in systems or infrastructure software.
• Ownership of a major subsystem spanning multiple components and teams.
• Deep expertise in storage data path or networking data path.

Responsibilities

• Own subsystem architecture and delivery plan across teams.
• Shape data path decisions across host, DPU software, firmware, and hardware.
• Lead delivery across component owners and guide engineers.
• Set end-to-end performance budgets and targets for throughput and tail latency.
• Ensure integration, observability, and production readiness for the subsystem.

Skills

C/C++

Linux

Performance analysis

Multicore architectures

Systems engineering

Storage/data path

Education

Bachelor's degree in Computer Science or Computer Engineering

Job description

Job Description

About the role

Oracle Cloud Infrastructure (OCI) is seeking a Senior Principal Software Engineer to build a new Data Processing Unit (DPU) platform spanning networking and storage. You will address system-level questions such as host-versus-DPU responsibilities, predictable tail latency under mixed workloads, and correct behavior across offload transitions, failures, and upgrades.

You will own a major subsystem spanning components and teams. Depending on the assignment, that could include a storage I/O pipeline, packet processing pipeline, host-to-DPU data path, or infrastructure acceleration subsystem. You will define architectural boundaries, align component owners, and remain accountable for integration and subsystem outcomes. We welcome engineers with deep storage data path expertise and working familiarity with networking, or deep networking data path expertise and working familiarity with storage. Your primary ownership will draw on your strengths while requiring collaboration across both domains.

What You Will Do

• Own subsystem architecture and outcomes. Turn ambiguous system requirements into an architecture, component contracts, and a phased delivery plan. Establish decision authority and resolve tradeoffs that individual component owners cannot settle independently.
• Shape foundational data path decisions. Evaluate partitioning across host, DPU software, firmware, and hardware. Validate choices about queueing, memory ownership, acceleration, and recovery through prototypes and representative workloads.
• Lead delivery across component owners. Decompose subsystem work, align technical dependencies, and resolve integration risks across teams. Guide implementation through other engineers while personally implementing or debugging critical paths.
• Set end-to-end performance expectations. Establish subsystem budgets and targets for throughput, tail latency, resource efficiency, and relevant storage I/O or packet processing metrics. Resolve bottlenecks that span component boundaries.
• Connect storage and networking architecture. Work with engineers in both domains to evaluate I/O processing, transport, ordering, buffering, backpressure, and recovery tradeoffs. Ensure local optimizations preserve end-to-end performance, availability, and data integrity.
• Own integration and production readiness. Lead subsystem qualification and technical readiness reviews. Establish compatible interfaces, observability, fault isolation, and safe upgrade behavior; resolve systemic risks during rollout and operation.
• Develop component owners. Mentor engineers in architectural judgment and systems debugging. Establish shared engineering practices and help component leaders make sound decisions independently.
• Establish reusable AI practices. Guide effective AI use across subsystem engineering work, with validation and clear accountability. Share approaches that improve quality and productivity, reduce repetitive debugging and documentation, and support employee well-being.

Required qualifications

• 10+ years of professional software engineering experience in systems or infrastructure software, including substantial hands-on experience building high-performance storage data paths or networking data paths.
• Demonstrated technical ownership of a major subsystem spanning multiple components and engineering teams, from ambiguous requirements through production integration.
• Deep expertise in either storage data path architecture, implementation, and optimization, or networking data path architecture, implementation, and optimization. Relevant experience may include storage I/O pipelines, block storage or storage transport, or high-performance packet processing and network virtualization.
• Strong hands-on C or C++ expertise and deep knowledge of Linux, synchronization, memory management, multicore architectures, and performance analysis.
• Working familiarity with the complementary domain: networking fundamentals and transport behavior for storage specialists, or storage I/O architecture and behavior for networking specialists. Ability to evaluate cross-domain performance and failure interactions with partner engineers.
• Experience defining component boundaries and contracts, establishing performance budgets, and resolving cross-component correctness and reliability issues.
• A record of driving technical alignment and delivery across teams while remaining actively involved in implementation and difficult debugging.
• Ability to explain complex architectural decisions and develop other engineers into effective component owners.
• A bachelor’s degree in Computer Science, Computer Engineering, or a related discipline, or equivalent practical experience.

Preferred qualifications

Experience in one or more of the following areas is valuable. Experience with every listed technology is not required.

• DPU architecture - DPUs, SmartNICs, AMD Pensando, NVIDIA BlueField/DOCA, P4, or comparable technologies; software, firmware, and hardware interface design.
• Packet processing - Architecture or substantial extension of DPDK-based systems or comparable user-space packet processing frameworks.
• Storage data paths - Storage I/O pipeline design or optimization, block storage, NVMe, NVMe over Fabrics, RDMA, or storage virtualization.
• Hardware and production - Hardware co-design, PCIe, DMA, SR-IOV, IOMMU, zero-copy techniques,