Lead Technical Program Manager

Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast‑paced environment of a true industry disruptor, you’ll find your place here. We value winning together—while learning, having fun, and making a profound difference for the dreamers and builders in the world. We are looking for a Lead Technical Program Manager to lead the data center build‑outs for our high‑density GPUs. You will be a driving force between hardware vendors, Data Center Architects, and the end‑to‑end oversight of doing a GPU Deployment. You’ll join a fast‑paced team dedicated to scaling our Agentic AI Cloud, making sure our physical hardware is deployed quickly and correctly to meet our customers’ heavy compute needs. What You’ll Be Doing Support hardware deployment projects for high‑density GPU clusters, coordinating the steps from early site planning all the way through the final rack‑and‑stack. Manage hardware delivery schedules tracking vendor lead times and working closely with the supply chain team to ensure servers and equipment arrive at the data center exactly when needed. Coordinate physical installations by partnering with colocation providers, remote hands, and internal networking teams to make sure space, power, and cables are prepped before hardware arrives. Act as the central hub of communication keeping supply chain, facilities, hardware engineers, and outside vendors aligned to keep deployment schedules on track. Help translate customer AI needs like the difference between building for training versus inference into clear deployment plans for our hardware and facility teams. Build repeatable deployment processes identifying logistical roadblocks and fixing them so we can consistently get new GPUs online faster. What We’ll Expect From You 10+ years of experience as a Technical Program Manager, successfully coordinating hardware, facilities, or data center infrastructure projects. Strong understanding of hardware deployment workflows, ideally from working at a cloud provider, colocation facility, or specialized AI company. Familiarity with basic data center concepts, meaning you understand the fundamentals of rack space, power limits, and cooling requirements needed for dense AI hardware. A solid grasp of the procurement lifecycle, including tracking orders, forecasting demand, and managing long lead times to ensure hardware shows up on time. Basic familiarity with the AI/ML hardware space, understanding why customers use GPUs and the high‑level physical differences required for training versus inference workloads. Experience with external vendor coordination, effectively working with colocation facility managers or remote hands to guide physical work happening off‑site. Strong risk management skills, with a proven ability to spot deployment risks early, whether it is a delayed hardware shipment or a facility constraint, and build plans to keep the project moving. Cross‑functional teamwork capabilities, acting as a reliable bridge between deeply technical teams (like network and data center engineering) and operational teams (like supply chain). Proficiency in project management tooling, feeling comfortable using standard tracking and ticketing systems to document deployment steps, track hardware inventory, and report on progress. Excellent communication and organization skills, with a proven ability to bring order to fast‑moving environments and keep diverse teams focused on a shared timeline. Compensation Range $148,000 - $186,000 This is a hybrid role JR: 2026-7922 DigitalOcean is an equal‑opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. #J-18808-Ljbffr