Teams at Lightning AI

Design and build backend systems for AI agent orchestration, tool execution, workflow management, memory, and state handling. Develop scalable APIs and reliable infrastructure for distributed AI workflows, improve platform reliability and observability, and partner with product, research, and engineering teams to deliver agent capabilities. Own technical initiatives from architecture through production, maintain software quality through testing and continuous delivery, and mentor engineers on backend and distributed-systems practices.

Develop and scale Lightning AI’s backend platform using Go, spanning APIs, infrastructure, billing, security, and integrations. Own features end to end, design reliable and scalable systems, improve architecture and performance, maintain software quality and continuous delivery, reduce technical debt, and mentor engineers. Collaborate with engineering, product, and design teams in a fast-changing SaaS environment.

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.