Teams at Lightning AI

Build and operate backend services, control planes, and automation for Lightning AI’s managed Kubernetes and Slurm infrastructure. Develop distributed systems for cluster provisioning, lifecycle management, scheduling, observability, reliability, and scalability across large-scale GPU environments. Diagnose complex production issues and collaborate with infrastructure, AI, and platform engineering teams. Contribute to architecture, technical design, mentoring, engineering practices, and on-call operations.

Designs and implements microservices-based platform services, RESTful APIs, backend systems, infrastructure automation, and cloud integrations. Responsibilities include architecture planning, monitoring and alerting, production troubleshooting, disaster recovery, performance optimization, code reviews, mentoring, and sprint planning. The role requires extensive experience with backend and distributed systems, cloud platforms, Kubernetes, microservices, programming languages, infrastructure as code, networking, security, and scalability.

Designs, deploys, automates, and operates large-scale NVIDIA InfiniBand fabrics for GPU clusters. Manages UFM, switches, firmware, congestion control, routing, QoS, observability, troubleshooting, capacity planning, and incident response. Collaborates with AI platform, GPU infrastructure, storage, and systems teams to build reliable AI Factory environments.