Senior Principal Engineer - AI Networking

You will work at the intersection of distributed systems, networking, and AI infrastructure, driving architecture, design, implementation, and performance optimization across software components that support thousands of GPUs and high-bandwidth network fabrics. The ideal candidate combines deep expertise in RDMA and distributed communication systems with a strong track record of delivering production-grade infrastructure at scale. As a technical leader, you will influence architecture across multiple teams, mentor senior engineers, and help shape the roadmap for Oracle's AI networking platform. What You'll Bring

• Ability to solve highly complex technical challenges spanning networking, distributed systems, and AI infrastructure.
• Strong system design skills with a focus on scalability, performance, and reliability.
• A data-driven approach to performance analysis and optimization.
• Excellent communication and collaboration skills across engineering organizations.
• Passion for building foundational technologies that enable the next generation of AI workloads.

Only Oracle brings together the data, infrastructure, applications, and expertise to power everything from industry innovations to life-saving care. And with AI embedded across our products and services, we help customers turn that promise into a better future for all. Discover your potential at a company leading the way in AI and cloud solutions that impact billions of lives. True innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing a workforce that promotes opportunities for all with competitive benefits that support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing [email protected] or by calling 1-888-404-2494 in the United States. 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. Oracle is seeking a highly experienced Lead Principal Software Engineer (IC5) to help define and build the next generation of AI networking infrastructure powering large-scale GPU clusters and distributed AI training platforms. This role focuses on high-performance networking, RDMA-based services, collective communication libraries, congestion management, resiliency, and software platforms that enable efficient operation of large-scale AI workloads. In this role, you will help build the networking and communication foundation for Oracle's AI infrastructure, enabling efficient scaling of cutting-edge AI workloads across large GPU clusters. Your work will directly influence the performance, reliability, and scalability of systems powering some of the industry's largest AI deployments. 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: $135,200 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.Career Level - IC5

Key Responsibilities

• Architect and develop high-performance networking software for large-scale AI and HPC environments.
• Design and implement RDMA-based services and infrastructure that enable low-latency, high-throughput communication across GPU clusters.
• Drive the evolution of collective communication frameworks and transport layers used by distributed AI training and inference workloads.
• Develop congestion management, traffic engineering, load balancing, and resiliency mechanisms for large-scale RDMA networks.
• Optimize end-to-end communication performance across networking, GPU, and software stacks.
• Collaborate with hardware, networking, distributed systems, and AI platform teams to deliver scalable infrastructure solutions.
• Lead performance analysis, bottleneck identification, and system-wide optimization efforts.
• Define architecture and technical direction for networking platforms supporting next-generation AI workloads.
• Build observability, monitoring, telemetry, and debugging capabilities for large-scale distributed systems.
• Drive reliability, fault tolerance, and recovery mechanisms for mission-critical AI infrastructure.
• Mentor engineers across the organization and provide technical leadership on complex cross-functional initiatives.
• Influence engineering best practices, architecture reviews, and long-term technology strategy.

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field; advanced degree preferred.
• 10+ years of software engineering experience building distributed systems, networking software, or infrastructure platforms.
• Deep expertise in RDMA technologies including RoCE, InfiniBand, or equivalent high-performance networking technologies.
• Strong experience developing networking software in C/C++.
• Experience designing and optimizing distributed communication frameworks and transport protocols.
• Solid understanding of operating systems, networking stacks, memory management, and performance optimization.
• Experience troubleshooting and optimizing large-scale production systems.
• Demonstrated technical leadership driving architecture and execution across multiple teams.
• Strong knowledge of Linux systems and low-level systems programming.

Preferred Qualifications

• Experience with collective communication libraries such as NCCL, RCCL, MPI, UCC, UCX, XCCL, or similar technologies.
• Experience building AI infrastructure supporting distributed training and inference workloads.
• Expertise in GPU networking technologies including GPUDirect RDMA and GPU-aware communication stacks.
• Experience with congestion management, adaptive routing, traffic shaping, and network resiliency mechanisms.
• Familiarity with large-scale GPU clusters consisting of hundreds to thousands of accelerators.
• Experience developing services and platforms operating directly over RDMA transports.
• Knowledge of distributed training frameworks such as PyTorch, DeepSpeed, Megatron-LM, TensorFlow, or JAX.
• Experience with cloud infrastructure and large-scale production service deployment.
• Familiarity with Kubernetes, containerized environments, and cloud-native infrastructure.
• Experience leading architecture for highly available and performance-critical systems.