Senior Software Engineer, AI Infra Management and Ops

Design, develop, and maintain cloud-native services and distributed systems that support platform capabilities, service lifecycle management, and operational excellence at scale. Collaborate across engineering organizations to help define technical direction and architecture for platform infrastructure, cloud services, networking, storage, compute, and operational excellence investments. Guide the development of platform engineering capabilities that improve deployment automation, service lifecycle management, observability, reliability, scalability, and developer productivity. Advance software engineering practices including Continuous Integration and Continuous Delivery (CI/CD), Infrastructure as Code (IaC), testing, security, monitoring, and operational readiness throughout the engineering lifecycle. Contribute to the design and operation of Artificial Intelligence (AI) infrastructure, High Performance Computing (HPC) platforms, bare-metal infrastructure, graphics processing unit (GPU) environments, and large-scale distributed computing systems. Collaborate on datacenter architecture and networking solutions, including rack-scale systems, network topology design, Ethernet fabrics, InfiniBand fabrics, Remote Direct Memory Access (RDMA), Smart Network Interface Cards (SmartNICs), Data Processing Units (DPUs), and accelerated computing platforms. Foster a culture of technical excellence through architecture collaboration, mentorship, knowledge sharing, design review participation, and support for engineering excellence across the broader organization 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#, Java, JavaScript, or Python OR equivalent experience. These requirements include but are not limited to the following specialized security screenings: Recognized for delivering technical solutions that span multiple engineering teams, organizations, or business areas. Demonstrated ability to simplify complex technical challenges and translate them into practical, scalable, and maintainable solutions. Proven ability to influence technical direction through collaboration, architectural leadership, technical mentoring, and cross-organizational partnerships. Knowledge of large-scale distributed systems, cloud-native platforms, or infrastructure services supporting business-critical production environments. Familiarity with Artificial Intelligence (AI) infrastructure, High Performance Computing (HPC) environments, accelerated computing platforms, or large-scale graphics processing unit (GPU) deployments. Knowledge of datacenter architecture, rack-scale infrastructure, network topology design, and modern datacenter networking technologies. Familiarity with InfiniBand fabrics, NVLink, NVSwitch, Ethernet networking, Remote Direct Memory Access (RDMA), Smart Network Interface Cards (SmartNICs), or Data Processing Units (DPUs) supporting large-scale compute environments. Understanding of bare-metal infrastructure, hardware lifecycle management, fleet operations, infrastructure telemetry, or platform operations at scale. Proficiency in one or more modern programming languages such as Go, Rust, C#, Java, or Python.