Sr. Software Engineer, EC2 Instance Networking

Job Description

Join our team building the scale-out networking backbone that powers the world's largest AI training clusters. We're developing high-performance RDMA and RoCE solutions that enable distributed training of trillion-parameter models across thousands of compute nodes on AWS infrastructure. As a senior engineer, you'll drive technical architecture decisions and lead the development of next-generation distributed AI training infrastructure.

Requirements

• Experience as a mentor, tech lead or leading an engineering team
• 5+ years of non-internship professional software development experience
• 5+ years of programming with at least one software programming language experience
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• 5+ years of programming experience in C/C++ with focus on high-performance distributed systems
• 5+ years of leading design or architecture of large-scale networked systems
• Deep expertise in RDMA technologies, RoCE implementations, and high-performance networking
• Extensive experience with collective communication libraries (NCCL, RCCL, OneCCL, MPI)
• Experience as a technical lead or leading engineering teams on complex infrastructure projects

Responsibilities

• Lead the design and development of high-performance networking software solutions utilizing RDMA and RoCE technologies for large-scale AI clusters
• Architect SmartNIC integration strategies with EC2 control plane systems and define API specifications
• Drive optimization of collective communication patterns and multi-rack networking protocols for distributed AI training
• Lead development of comprehensive performance monitoring, metrics collection, and benchmarking infrastructure
• Design automated testing frameworks and stress testing methodologies for large-scale distributed systems
• Lead complex system-level debugging efforts across hardware acceleration, kernel networking, and distributed applications
• Define technical architecture and strategy for next-generation scale-out AI cluster networking
• Provide technical leadership and mentoring to engineering teams
• Drive cross-functional collaboration with hardware, cloud infrastructure, and AI platform teams
• Lead technical design reviews and establish engineering best practices

Benefits

• Medical, dental, and vision coverage (multiple plan options)
• Health savings and flexible spending accounts
• 24/7 Employee Assistance Program for mental health support
• 401(k) with company match and various investment choices
• Company-paid life/AD&D and disability insurance
• Restricted stock units (RSUs) for employee ownership
• Child care and elder care referrals, adoption assistance
• Paid maternity and parental leave (including Ramp Back)
• Paid time off (PTO) and company holidays
• Employee discount on Amazon.com products
• Career Choice program (95% tuition and textbook coverage)