高级软件工程师，网络平台

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 foundational 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.

• Research Cluster Networking: Design and implement networking systems for research computing environments including Kubernetes and SLURM clusters, enabling high-performance connectivity, optimized network topology for distributed workloads, and seamless integration with cluster orchestration systems.

• 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.

• Network Observability: Implement comprehensive network monitoring, telemetry, and troubleshooting systems that provide visibility into network performance, utilization, and tenant traffic patterns.Security & Policy Management: Build platform network security features including security groups, firewall rules, and policy enforcement that protect tenant workloads while enabling flexible network configuration.

Requirements:

• Experience: 5+ years in software engineering with proven experience building network platforms, SDN systems, or network automation for production environments.

• Kubernetes Networking & Container Orchestration: Strong familiarity with Kubernetes networking architecture, CNI plugins, service networking, and network policies. Understanding of pod networking, services, ingress, and how Kubernetes manages network resources.

• Networking Expertise: Deep understanding of networking fundamentals including TCP/IP, VLANs, VXLAN, BGP, OSPF, routing protocols, and data center network architectures.Software-Defined Networking: Background in SDN concepts, network virtualization, overlay networks, and programmable networking technologies.

• Programming Skills: Experience with Go and Python for performance-critical networking components and services is highly valued.

• Linux Networking: Strong experience with Linux networking stack, including network namespaces, iptables/nftables, Open vSwitch, and kernel networking systems.

• DPU & SmartNIC Experience: Familiarity with DPU/SmartNIC architectures (Bluefield, or similar), SR-IOV, hardware offload capabilities, and programmable networking hardware – or strong ability to learn quickly.

• High-Performance Networking: Understanding of RDMA, RoCE, Infiniband, and low-latency networking requirements for distributed computing and GPU workloads.

• Problem-Solving & Architecture: Demonstrated ability to solve complex networking performance and scalability challenges while balancing pragmatic shipping with good long-term architecture.

• Autonomy & Communication: Comfortable navigating ambiguity, defining requirements collaboratively, and communicating technical decisions through clear documentation.

• Commitment to Growth: Growth mindset with continuous focus on learning and professional development.

Preferred Qualifications

• Background provisioning or managing networking for research computing environments (Kubernetes, SLURM, or HPC clusters)

• Experience with NVIDIA Bluefield DPU programming and DOCA framework

• Background with network function virtualization (NFV) and service function chaining

• Knowledge of Kubernetes networking (CNI plugins, network policies, service mesh)

• Experience building network control planes or SDN controllers

• Familiarity with network automation frameworks and infrastructure-as-code for networking

• Understanding of data center fabric architectures (spine-leaf, CLOS topologies)

• Experience with network security and compliance requirements in regulated industries

• Background building networking for research institutions, HPC environments, or cloud providers

Key Technologies
· Go, Python, NVIDIA Bluefield DPUs, Open vSwitch, VXLAN, SR-IOV, RDMA, RoCE, InfiniBand, BGP, Linux networking, Terraform, FastAPI, gRPC
Why Moonlite

• Build Next-Generation Infrastructure: Your work will create the platform foundation that enables financial institutions to harness AI capabilities previously impossible with traditional infrastructure.

• Hands-On Ownership: As an early engineer, you’ll have end-to-end ownership of projects and the autonomy to influence our product and technology direction.

• Shape Industry Standards: Contribute to defining how enterprise AI infrastructure should work for the most demanding regulated environments.

• Collaborate with Experts: Work alongside seasoned engineers and industry professionals passionate about high-performance computing, innovation, and problem-solving.

• Start-Up Agility with Industry Impact: Enjoy the dynamic, fast-paced environment of a startup while making an immediate impact in an evolving and critical technology space.

We offer a competitive total compensation package combining a competitive base salary, startup equity, and industry-leading benefits. The total compensation range for this role is $165,000 – $225,000, which includes both base salary and equity. Actual compensation will be determined based on experience, skills, and market alignment. We provide generous benefits, including a 6% 401(k) match, fully covered health insurance premiums, and other comprehensive offerings to support your well-being and success as we grow together.
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Originally posted on Himalayas