Software Engineer

Moonlite delivers high-performance AI infrastructure for organizations running intensive computational research, large-scale model training, and demanding data processing workloads. We provide infrastructure deployed in our facilities or co-located in yours, delivering flexible on-demand or reserved compute that feels like an extension of your existing data center. Our team of AI infrastructure specialists combines bare-metal performance with cloud-native operational simplicity, enabling research teams and enterprises to deploy demanding AI workloads with enterprise-grade reliability and compliance.

Your Role:

You will be fundamental to building our software-defined networking (SDN) platform that enables high-performance, isolated networking for distributed computing, model training, inference, and data-intensive workloads. Working closely with our network, infrastructure, and product teams, you'll design and implement the network orchestration and provisioning systems that manage DPU-accelerated networking, tenant isolation, and network lifecycle management, enabling researchers and engineers to access enterprise-grade networking with cloud-like simplicity.

Job Responsibilities

• Software-Defined Networking Architecture: Collaborate with infrastructure to design and build scalable SDN orchestration systems leveraging NVIDIA Bluefield-3 DPUs to deliver programmable, high-performance networking for AI workloads with hardware-accelerated forwarding isolation.
• Network Provisioning & Lifecycle Management: Implement automated SDN provisioning systems that handle VPC creation, subnet allocation, routing configuration, and network resource lifecycle from deployment through decommissioning.
• DPU Platform Engineering: Develop platform capabilities for managing Bluefield-3 DPUs including SR-IOV virtual function management, OVS offload configuration, network function deployment, and integration with compute orchestration systems.
• Multi-Tenancy & Network Isolation: Build enterprise-grade network isolation using VPCs, VXLAN, and hardware-accelerated forwarding to ensure complete tenant separation while maintaining high-performance connectivity for GPU clusters and distributed workloads.
• High-Performance Networking: Collaborate with infrastructure to optimize network paths for RDMA, RoCE, and GPU-to-GPU communication, ensuring minimal latency and maximum throughput for distributed training and large-scale computational workloads.
• Network APIs & Integration: Develop robust APIs and SDKs for network resource management that integrate seamlessly with compute and storage platforms, enabling programmatic network provisioning and configuration.