Senior Software Engineer, Platform Infrastructure

You will be foundational to building the comprehensive infrastructure platform that bridges our physical infrastructure – bare-metal servers, GPU clusters, high-performance storage, and networking fabric – with the systems our customers depend on for large-scale computation, inference, simulations, and training. Working closely with product, your platform team members, and infrastructure specialists, you’ll design and implement the orchestration layer, APIs, and automation framework that make thousands of servers, petabytes of storage, and high-speed networks feel like a unified, programmable platform.

• Infrastructure Abstraction Layer: Design and build systems that bridge physical infrastructure (bare-metal servers, storage clusters, network fabric) with customer-facing services, enabling programmatic management of compute, networking, and storage at scale.
• Research Cluster Provisioning: Design and implement systems for provisioning and managing research computing environments including Kubernetes and SLURM clusters, enabling automated deployment, resource scheduling, and workload orchestration for distributed AI training and HPC workloads.
• Platform Orchestration: Implement comprehensive orchestration systems that coordinate across compute, storage and networking to deliver unified experience for complex research workloads.
• Network Automation & Placement: Design and build network provisioning automation including intelligent VM placement decisions for optimal network topology, automated VLAN and subnet configuration, and software-designed networking orchestration for high-performance interconnects.
• Enterprise APIs & SDKs: Develop robust APIs and SDKs that enable researchers and engineering teams to programmatically provision and manage infrastructure resources across all platform domains.
• Observability & Telemetry: Implement comprehensive observability, telemetry, and logging systems that provide visibility into infrastructure health, performance, and utilization across the infrastructure footprint.
• Performance Engineering: Build and optimize platform services that deliver consistent high-throughput low-latency networking for demand research applications and data-intensive workloads.
• Cross-Team Collaboration: Work closely with engineering, infrastructure, and product to define requirements, drive infrastructure-product-rollouts, and improve resource lifecycle management.
• Compliance & Security: Implement platform-wide compliance and security features supporting SOC 2, ISO 27001, and enterprise regulatory requirements including comprehensive audit logging, access controls, and data residency management.

• Experience: 5+ years in software engineering with a proven track record of infrastructure platforms, distributed systems, or cloud platforms for production environments.
• Kubernetes & Container Orchestration: Strong familiarity with Kubernetes architecture, container orchestration concepts, and experience deploying workloads in Kubernetes environments. Understanding of pods, deployments, services, and basic Kubernetes operations.
• Infrastructure Systems: Strong understanding of infrastructure fundamentals including compute orchestration, storage systems, networking technologies, and how they integrate together to deliver complete platform experiences.
• Programming Skills: Experience with systems programming languages (Go, C/C++, Rust, Python) for performance-critical components is a strong plus.
• Linux Production Experience: Strong experience with linux in production environments, including systems administration, performance tuning, and troubleshooting.
• Bare-Metal & Virtualization: Deep knowledge of bare-metal infrastructure, provisioning systems, out-of-band management, and virtualization technologies (KVM, Kubernetes, etc).
• API & Platform Design: Proven experience designing and building APIs, SDKs, and automation frameworks that enable programmatic infrastructure management.
• Cloud Platform Knowledge: Strong familiarity with cloud environments (AWS, GCP, Azure) and understanding of how to translate cloud-native patterns to bare-metal infrastructure.
• Infrastructure Automation: Experience with Infrastructure-as-code tools (Terraform, Ansible) and building automated deployment pipelines.
• Problem Solving & Autonomy: Self-starter who can navigate ambiguity, balance pragmatic shipping with good long-term architecture, and independently drive complex technical initiatives.
• Communication Skills: Strong written and verbal communication skills, including ability to write clear technical communication and collaborate across teams.
• Commitment to Growth: Growth mindset with continuous focus on learning and professional development.

• Background provisioning or managing research computing environments (Kubernetes, SLURM, or HPC clusters)
• Experience building internal platforms, infrastructure-as-a-service, or developer tooling
• Background with GPU computing platforms and AI/ML infrastructure requirements
• Knowledge of high-performance networking technologies (InfiniBand, RDMA, SR-IOV)
• Experience with observability and monitoring platforms (Prometheus, Grafana, ELK stack)
• Familiarity with both cloud-native and bare-metal infrastructure deployment models
• Understanding of enterprise compliance requirements and security best practices
• Extra points for experience with financial services technology infrastructure and understanding of trading system requirements

• Go, Python, Kubernetes, Docker, Terraform, Ansible, Linux, Networking (BGP, VXLAN), Storage Systems, FastAPI, PostgreSQL, Redis, NVIDIA GPU Technologies, InfiniBand

• 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.

Moonlite builds the infrastructure behind ambitious AI.

We design, deploy, and operate high-performance GPU systems for large-scale model training, computational research, and intensive data workloads. We combine bare-metal performance with the reliability and simplicity teams expect from the cloud.

What’s next in AI needs matching infrastructure. We’re building the team to make it happen.