Senior Software Engineer, Platform Infrastructure

Moonlite AI builds high-performance AI infrastructure for computational research, model training, and data processing. The Senior Software Engineer, Platform Infrastructure will build the platform that connects physical compute, storage, and networking infrastructure with customer-facing services, including orchestration, APIs, automation, and observability.

Responsibilities:

• 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

Requirements:

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