Principal Technical Program Manager (Quantum)

## About the role Drive Program Execution & Delivery Lead end-to-end execution of complex hardware development programs, ensuring clear milestones, dependency management, and disciplined, predictable delivery across the 1P Quantum stack—while proactively identifying and mitigating technical and program risks ## Strategic Planning & Roadmapping Define and drive program strategy and roadmaps across the 1P Quantum stack, setting direction, priorities, and success criteria in partnership with technical leadership to guide the transition from research to scalable, production-ready systems ## Cross-Disciplinary Coordination & Alignment Facilitate collaboration across quantum physicists, device engineers, process development engineers, systems engineering, and partners—bringing clarity to complex spaces and driving alignment across stakeholders and leadership to enable reliable, scalable hardware solutions ## Supplier & Partner Management AI-Driven Development Acceleration Identify and drive opportunities to leverage AI, machine learning, and automation to optimize engineering workflows, improve decision-making, and increase development velocity across the hardware stack ## Data, Quality & Yield Excellence Drive a data-informed approach to program and engineering execution, and lead systemic improvements in quality, yield, and reliability by scaling industry best practices e.g., root cause analysis, statistical methods, yield optimization, enabling efficient scale-up from development to manufacturing ## Other Doctorate in Physics, Engineering, or related field AND experience in hardware development, technical program management, quantum physics (or related field) OR Master's Degree in Physics, Engineering, or related field AND significant experience in hardware development, technical program management, quantum physics (or related field) ## Requirements - Demonstrated experience driving complex, cross-functional programs with multiple stakeholders and dependencies across organizational boundaries - Technical depth in advanced hardware or experimental systems, such as device development, semiconductor manufacturing, measurement and control systems, or related quantum or semiconductor domains - Experience driving technology transfer from R&D into engineering and manufacturing, including system integration, new product introduction (NPI), and production readiness - Proven experience leading complex, multi-year hardware programs in deep-tech or first-of-a-kind domains (e.g., quantum systems, ASICs, photonics, advanced packaging, cryoelectronics, or other high-reliability hardware), with end-to-end ownership from concept through scale-up - Experience improving hardware quality, yield, and reliability, particularly in early-stage or scaling technologies transitioning toward manufacturing, using data-driven approaches and industry-standard methodologies (e.g., root cause analysis, statistical process control, yield optimization) - Program management foundations in complex, matrixed environments, including planning, dependency management, risk tracking, and executive communication - Experience leveraging data, automation, or AI to improve engineering or program execution, with an understanding of how modern tooling can accelerate development workflows and enhance decision-making - Experience working with fabrication and manufacturing ecosystems, particularly in advanced semiconductor or emerging hardware environments, including supply chains, contract manufacturers, R&D foundries, or advanced materials partners - Ability to leverage AI tools to drive innovation and efficiency (e.g., performance modelling and analysis, research gathering, day to day task automation) - Ability to work in an "AI-first" environment using modern AI tools to accelerate discovery through hardware development