SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Fluidstack is building civilization-scale AI compute infrastructure, acquiring power, designing and operating data centers at unprecedented speed and scale. The Product Engineering NPI (New Product Introduction) Team is responsible for taking hardware from design release to repeatable production across all Fluidstack products, ranging from compute racks to medium-voltage switchgear.
As NPI Team Lead, you will build the NPI process from scratch, defining stage-gate processes, readiness criteria, and change discipline (ECOs, deviations) that work across diverse product families without forcing them through identical checklists. You'll lead and develop a small TPM (Technical Program Manager) team, allocating 3 TPMs across 6 concurrent product families while managing portfolio-level visibility and risk reporting.
Key responsibilities include: establishing transfer-to-manufacturing standards with manufacturing engineering; defining exit criteria programs must clear before production takes ownership; holding clear RACI between TPMs and engineering technical leads to eliminate ownership ambiguity; and maintaining portfolio-level program visibility with rigorous status and risk reporting that surfaces problems to leadership proactively.
The role requires someone who has built stage-gate processes from first principles (not just operated within existing ones), led and developed TPM/NPI teams, managed multiple concurrent product lines, and understands how to keep NPI processes lightweight enough that engineers use them rather than route around them. You should have experience killing programs when necessary and can articulate what signals you missed and now monitor. Bonus experience includes portfolio management tooling, products spanning compute and power equipment, manufacturing transfer at new plants, and building teams from zero.
Fluidstack operates with extreme ownership, full autonomy, velocity, first-principles thinking, and a focus on the frontier of AI as the most interesting problem of our time.
