Job Description
Are you ready to engineer the future? Nexus Future Systems is pioneering the 2026 technology stack and is seeking a visionary Lead Quantum AI Architect to spearhead our next-generation computational initiatives. In this role, you will bridge the gap between theoretical quantum mechanics and practical artificial intelligence, building scalable systems that redefine the boundaries of computation.
We are looking for a technical leader who thrives in ambiguity and is passionate about solving the world's most complex problems using advanced algorithms. If you have a deep understanding of quantum hardware/software ecosystems and a track record of leading high-performance engineering teams, we want to hear from you.
Responsibilities
- Architect Next-Gen Systems: Design and implement proprietary quantum algorithms integrated with classical AI models to optimize performance for the 2026 computing landscape.
- R&D Leadership: Lead a cross-functional team of quantum physicists, data scientists, and software engineers in exploring new frontiers in quantum machine learning.
- Hardware Integration: Collaborate with hardware vendors to ensure software compatibility with next-gen quantum processors and edge devices.
- Scalability Strategy: Develop strategies for quantum error correction and resource management to ensure robust deployment in cloud and hybrid environments.
- Talent Development: Mentor junior engineers and establish best practices for quantum software engineering within the organization.
- Client Solutions: Translate complex technical requirements into actionable development roadmaps for enterprise clients.
Qualifications
- Education: Master’s or PhD in Computer Science, Physics, Mathematics, or a related field with a focus on Quantum Computing or Artificial Intelligence.
- Experience: 7+ years of experience in software engineering, with at least 3 years specifically in quantum computing or advanced AI development.
- Technical Stack: Proficiency in Python, C++, Qiskit, Cirq, or similar quantum programming frameworks; deep knowledge of TensorFlow, PyTorch, or similar ML libraries.
- Leadership: Proven experience leading engineering teams and managing project lifecycles from conception to deployment.
- Problem Solving: Exceptional analytical skills with a demonstrated ability to tackle complex, novel problems.
- Communication: Excellent written and verbal communication skills, capable of presenting complex concepts to non-technical stakeholders.