Senior Software Engineer

Design, develop, and optimize networking solutions tailored for large-scale AI training infrastructure. Architect and implement high-performance, low-latency, and low-jitter communication frameworks for distributed systems. Benchmark, analyze, and enhance the scalability and reliability of networking systems to handle petabyte-scale data transfer. Debug and resolve complex networking issues in large-scale, high-performance environments. Drive identification of dependencies and the development of design documents for a product, application, service, or platform. Create, implement, optimize, debug, refactor, and reuse code to establish and improve performance and maintainability, effectiveness, and return on investment (ROI). Act as a Designated Responsible Individual (DRI) and guides other engineers by developing and following the playbook, working on call to monitor system/product/service for degradation, downtime, or interruptions, alerting stakeholders about status and initiates actions to restore system/product/service for simple and complex problems when appropriate. Proactively seek new knowledge and adapts to new AI trends, technical solutions, and patterns that will improve the availability, reliability, efficiency, observability, and performance of products while also driving consistency in monitoring and operations at scale. Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, OR Java, JavaScript, or Python OR equivalent experience. Bachelor's Degree in Computer Science OR related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, OR Python OR Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. In-depth understanding of networking protocols (e.g., Ethernet, TCP/IP, RDMA, gRPC) and distributed systems. Familiarity with network virtualization, software-defined networking (SDN), or network performance tuning. Hands-on experience with networking technologies in AI-specific hardware (e.g., InfiniBand, ROCE, NVLink). Familiarity with AI accelerators such as GPUs (NVIDIA, AMD) or TPUs, and how they interact with networking infrastructure. Experience with telemetry and observability tools for network monitoring at scale. Background in building scalable and fault-tolerant systems in large, distributed environments.