Senior Software Engineer, Network Platform

Moonlite AI; United States; On-site; USD 165,000 - 225,000; Full time

Benefits offered by this job

6% 401(k) match

Fully covered health insurance premiums

Startup equity

Job summary

A leading AI infrastructure company seeks an experienced software engineer to build software-defined networking systems for demanding AI workloads. This role involves collaborating on scalable SDN orchestration systems and optimizing networking for distributed computing. Candidates should have over 5 years of experience in software engineering, deep networking knowledge, and programming skills in Go or Python. The position offers competitive compensation and generous benefits.

Qualifications

• 5+ years in software engineering with experience building network platforms.
• Strong familiarity with Kubernetes networking architecture.
• Deep understanding of networking fundamentals including TCP/IP and routing protocols.
• Experience with Go and Python is highly valued.
• Experience with Linux networking stack and Open vSwitch.
• Familiarity with DPU architectures preferred.
• Understanding of low-latency networking requirements for distributed computing.

Responsibilities

• Collaborate with infrastructure to design SDN orchestration systems.
• Implement networking systems for research computing environments.
• Develop platform capabilities for managing Bluefield-3 DPUs.
• Build enterprise-grade network isolation using VPCs and VXLAN.
• Optimize network paths for RDMA and GPU-to-GPU communication.
• Develop APIs for network resource management.
• Implement network monitoring and troubleshooting systems.

Skills

Software engineering

Kubernetes networking

Networking fundamentals

Programming in Go and Python

Linux networking

DPU/SmartNIC architecture

Problem-solving

Communication

Tools

NVIDIA Bluefield DPUs

Open vSwitch

Terraform

FastAPI

gRPC

Job description

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. 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.