Principal Quantum Architect

Analyze qubit tuning and quantum circuit execution flows in measurement-based topological quantum systems, translating system-level needs into scalable architectural requirements. Define and drive subsystem requirements for the readout, control, and orchestration software layers, ensuring alignment with system performance, scalability, and operational goals. Analyze performance and scaling through scaling analysis, behavioral modeling, and rapid prototyping. Communicate architectural concepts, tradeoffs, and recommendations effectively across a multi-disciplinary team. Leverage modern AI tools to support architectural validation, rapid prototyping, performance analysis, and engineering productivity. Doctorate in Physics, Engineering, or related field AND 3+ years experience in industry or in a research and development environment OR Master's Degree in Physics, Engineering, or related field AND 6+ years experience in industry or in a research and development environment OR Bachelor's Degree in Physics, Engineering, or related field AND 8+ years experience in industry or in a research and development environment OR equivalent experience. Ability to use AI tools to improve engineering productivity, including performance analysis, research synthesis, and routine workflow automation. Ability to work effectively in an AI-first environment by incorporating modern AI tools into day-to-day hardware development and decision-making. Familiarity with quantum algorithms and quantum error correction as well as an understanding of how they are executed in real-world settings. Understanding of end-to-end system architecture for quantum computing platforms, including how requirements flow down from system goals to subsystem and component specifications. Strong scientific programming skills, including experience developing software for complex research environments and contributing to codebases that support experimentation and long-term maintainability. Experience with performance-aware software design and scaling computational workflows, including parallel, distributed, or high-performance computing environments. Demonstrated ability to leverage modern AI tools for rapid prototyping