Job Description
We are on the brink of a new technological era. As we approach the year 2026, the convergence of Artificial Intelligence and Quantum Computing is set to redefine the boundaries of possibility. Nexus 2026 Labs is a forward-thinking research and development firm dedicated to building the infrastructure of tomorrow. We are seeking a visionary Senior AI & Quantum Solutions Architect to lead our engineering division and bridge the gap between theoretical physics and practical AI deployment.
In this role, you will not just be writing code; you will be architecting the future of high-performance computing. You will work directly with our quantum hardware team to develop algorithms that leverage qubit stability and coherence, while integrating them into robust, scalable classical AI frameworks.
Why Join Us?
- Work on cutting-edge technology that will define the next decade.
- Competitive equity package and performance-based bonuses.
- Flexible remote-first policy with quarterly team meetups in Silicon Valley.
- State-of-the-art equipment and access to quantum cloud resources.
Responsibilities
- Design and implement complex hybrid AI/Quantum architectures capable of solving problems intractable for classical systems.
- Lead the technical roadmap for our proprietary quantum processing unit (QPU) integration layers.
- Mentor a team of elite software engineers and data scientists, fostering a culture of innovation and rigorous engineering standards.
- Collaborate with cross-functional teams (hardware, product, security) to ensure seamless deployment of quantum-enhanced machine learning models.
- Conduct high-level research and proof-of-concept studies to validate new algorithms before full-scale production.
- Optimize classical Python/C++ codebases to function efficiently as the backend for quantum computations.
Qualifications
- PhD or Master’s degree in Computer Science, Physics, Applied Mathematics, or a related field with a focus on Quantum Information Science.
- Minimum of 10 years of experience in software architecture, with at least 5 years specifically in AI/ML and distributed systems.
- Strong proficiency in Python, C++, and CUDA.
- Experience with quantum computing frameworks (Qiskit, Cirq, or PyQuil) and quantum simulators.
- Deep understanding of machine learning algorithms, neural networks, and their optimization for edge devices.
- Proven track record of leading high-performance engineering teams in a fast-paced environment.