Moonlite AI
Senior Software Engineer, Network Platform
Moonlite AI, Chicago, Illinois, United States, 60290
Senior Software Engineer, Network Platform
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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:
Expert-level Python proficiency. Experience with Go 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
Python, Go, 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.
Seniority level Mid-Senior level
Employment type Full-time
Job function Engineering and Information Technology
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Get AI-powered advice on this job and more exclusive features.
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:
Expert-level Python proficiency. Experience with Go 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
Python, Go, 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.
Seniority level Mid-Senior level
Employment type Full-time
Job function Engineering and Information Technology
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