Job Description
We are on the precipice of a technological singularity. At Nexus Horizon Labs, we are not just predicting the future; we are architecting it. As part of our exclusive 'Year 2026' strategic initiative, we are seeking a visionary Chief Architect to spearhead the convergence of Artificial Intelligence and Quantum Mechanics. This is a rare opportunity to define the foundational infrastructure of the next industrial revolution.
In this pivotal role, you will lead a world-class team of physicists, engineers, and data scientists to develop scalable quantum neural networks capable of solving complex optimization problems in real-time. You will bridge the gap between theoretical physics and practical software engineering, ensuring our solutions are robust, scalable, and transformative.
Responsibilities
- Lead the architectural design and implementation of hybrid quantum-classical machine learning systems for the 2026 initiative.
- Define the technical vision and roadmap for quantum computing infrastructure, ensuring alignment with business objectives.
- Oversee the performance tuning of quantum algorithms, optimizing qubit coherence and error correction protocols.
- Mentor and mentor senior engineering talent, fostering a culture of innovation and technical excellence.
- Collaborate with cross-functional stakeholders, including product managers and data scientists, to translate abstract research into deployable products.
- Establish best practices for security, scalability, and interoperability in next-gen computing environments.
- Represent the company at industry conferences and technical forums, establishing thought leadership in the quantum space.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Physics, Mathematics, or a related quantitative field with a focus on quantum mechanics.
- Extensive experience (5+ years) in software architecture, with a specific focus on high-performance computing or distributed systems.
- Deep technical proficiency in quantum computing frameworks such as Qiskit, Cirq, or PyQuil.
- Strong background in machine learning, neural networks, and deep learning algorithms.
- Proven track record of leading engineering teams and delivering complex systems under tight deadlines.
- Experience with cloud infrastructure (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes).
- Exceptional problem-solving skills and the ability to thrive in an ambiguous, fast-paced, research-driven environment.