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This is a general talent community opportunity rather than a specific open position. Lightning AI invites candidates to submit their information for consideration as future roles become available across U.S. and London hubs, with occasional remote opportunities. The company develops tools and infrastructure for building, training, and deploying AI systems and values ownership, urgency, communication, teamwork, continuous improvement, and long-term thinking.

Design, optimize, and deploy large language model training and post-training pipelines. Improve model quality through fine-tuning, reinforcement learning, preference optimization, evaluation, and experimentation. Build PyTorch-based infrastructure, optimize distributed multi-GPU training, diagnose performance and convergence issues, and develop production-ready AI systems. Collaborate with researchers, infrastructure engineers, platform teams, and customers while contributing to open-source projects and reusable training capabilities.

Build, validate, and operate large-scale bare-metal GPU infrastructure for AI/ML and HPC workloads. Responsibilities include managing Linux systems, image pipelines, test clusters, provisioning, firmware and driver validation, GPU diagnostics, performance analysis with NVIDIA DCGM, automation, virtualization, and hardware management interfaces. The role requires troubleshooting across hardware and software layers while collaborating with infrastructure, hardware, data center, platform, and ML teams.

Operate, scale, and optimize distributed storage infrastructure supporting large-scale AI/ML and HPC workloads. Build Python automation, manage Linux bare-metal systems, troubleshoot storage, hardware, networking, and operating system issues, and improve performance, reliability, monitoring, capacity planning, and lifecycle management. Collaborate with infrastructure, networking, platform, and data center teams on storage deployments and scaling strategies.

Own revenue accounting and AR operations for a consumption-based GPU cloud business. Responsibilities include revenue close, ASC 606 technical accounting, CRM-to-cash data integrity, billing and collections, usage-to-cash reconciliations, contract cost accounting, audit support, historical revenue recasting, and building scalable CRM, billing, ERP, controls, and documentation processes.

The Senior People Partner will support engineering and technical leaders on organizational design, leveling, promotions, compensation, employee relations, performance management, and exits. The role will strengthen manager capabilities, improve technical hiring practices, build scalable people systems, and manage global employment complexity. This position requires strong judgment, communication, and influence in a fast-scaling, distributed AI and technology company.

Drives strategic finance, corporate development, and FP&A initiatives, including pricing, unit economics, GPU financing, M&A diligence, investor communications, and capital allocation. Builds and maintains financial models, leads reporting and forecasting cycles, supports annual and long-range planning, evaluates CapEx and infrastructure investments, and delivers executive-level insights on business performance, risks, and opportunities.

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 review, mentoring, and participation in technical planning. Requires strong experience with distributed systems, AWS, GCP or Azure, Kubernetes, microservices, programming in Go, Python or Java, infrastructure as code, networking, security, and scalability.

Operate and scale large GPU infrastructure platforms, including Linux systems, bare-metal environments, provisioning workflows, observability, and reliability automation. Responsibilities include platform deployment, incident response, break/fix operations, customer provisioning, on-call participation, infrastructure troubleshooting, and collaboration across engineering, networking, customer success, and software teams. The role also develops automation to reduce manual work and improve operational efficiency.

Own cross-functional operations projects that remove growth blockers, diagnose organizational friction, and build scalable AI-powered internal tools and automations. Partner with teams across the company, drive project adoption, maintain internal operations documentation, support business programs, and measure outcomes using data. The role requires strong analytical thinking, stakeholder management, end-to-end project ownership, and hands-on experience building workflows with APIs, SaaS platforms, automation tools, and AI coding tools.