Lead/Principal Platform Architect

Job description

Join Qutwo - Europe's private Quantum AI Lab , on our quest to bridge the gap between the classical and the quantum world. We partner with the most advanced and forward-thinking customers, solving fundamental real-world problems, side by side. The best scientists and engineers in the world are drawn to one thing: a problem worthy of their ability. At Qutwo, we have one. We are a European AI lab for the quantum era, co-founded by pioneers behind IQM and Silo AI, with a team spanning MIT, UC Berkeley, Cambridge, and Carnegie Mellon, and backed by the founders of Skype, Hugging Face, Quantinuum, Supercell and many more. We work at the intersection of quantum computing, AI, optimization, and simulation — where the answers do not yet exist and the work genuinely matters. We are seeking an exceptional Lead Architect to design the foundation of our hardware-aware quantum computing platform. If you thrive at the intersection of software architecture and cutting-edge quantum technology, this is for you. Our main office is located in Helsinki. Role Description As Lead Architect, you will design the core architecture of Qutwo OS — the abstraction layer that enables seamless execution across quantum backends such as IBM, IQM, IonQ, D-Wave, and Quantinuum. Working closely with the CTO and Head of Research, you will define the technical blueprint that transforms research innovations into a production-ready platform. You will also lead and mentor the platform engineering team. Qualifications Minimum 10 years of software architecture experience, with 3+ years in quantum computing. Deep understanding of quantum hardware and software architectures. Deep understanding of MLOps and ML/GenAI training pipelines. Experience with quantum intermediate representations (OpenQASM, QIR, or similar). Proficiency with quantum SDKs (Qiskit, Cirq, PennyLane). Strong background in distributed systems and API design. Experience with cloud-native architectures (Azure/AWS/GCP, cloud security, Terraform, Kubernetes, microservices). Excellent communication skills to articulate complex technical concepts. MSc or PhD in Computer Science, Physics, or related field preferred. Experience in one or more of the following areas is a plus but not a requirement: Compiler design or circuit optimization. Training and deploying deep learning models, including LLMs High-performance computing (HPC) systems. Enterprise platform development.