Teams at Lightning AI

Operate and scale GPU infrastructure platforms across Linux, bare-metal, cloud, and Kubernetes environments. Design reliable platforms, automate provisioning and operational workflows, deploy improvements, manage observability, respond to incidents, and participate in on-call rotations. Collaborate with infrastructure, networking, customer success, and software teams while troubleshooting complex systems and balancing design, risk, cost, and business outcomes.

Support ML engineering teams running production training and inference workloads across Kubernetes, cloud, Linux, and GPU infrastructure. Diagnose distributed PyTorch, CUDA, NCCL, networking, storage, scheduling, and performance issues; analyze observability data; advise customers during incidents; and improve reliability through tooling, automation, documentation, runbooks, and operational processes. The role is hybrid in London, requires at least two office days weekly, and supports EMEA shifts.

Own customer health, adoption, retention, renewal readiness, expansion influence, and executive relationships. Build scalable customer success processes covering onboarding, success planning, business reviews, health scoring, forecasting, escalations, and expansion handoffs. Partner with Sales, Product, Engineering, Support, and other teams to improve customer outcomes, develop playbooks, provide roadmap feedback, and establish a proactive, technically informed customer success culture.