Job Description
Are you ready to architect the future of intelligence?
Nexus Horizon is seeking a visionary Lead AI & Quantum Integration Engineer to join our elite R&D division. In this pivotal role, you will bridge the gap between classical computing and next-generation quantum architectures, defining the operational standards for 2026 and beyond. If you thrive in high-pressure environments and are passionate about pushing the boundaries of what is computationally possible, we want to hear from you.
Our mission is to build the foundational infrastructure for the post-silicon era. You will lead a cross-functional team of AI researchers and quantum physicists to develop scalable systems capable of solving the world's most complex problems.
Responsibilities
- Architect Hybrid Systems: Design and implement scalable integration layers between classical AI models and emerging quantum processors.
- Pioneer Quantum Algorithms: Develop proprietary algorithms to optimize quantum circuit efficiency and reduce decoherence latency.
- Lead Technical Vision: Define the technical roadmap for AI/Quantum convergence, ensuring alignment with business objectives and industry standards.
- Mentor Elite Talent: Recruit, mentor, and retain top-tier engineering talent, fostering a culture of innovation and excellence.
- Performance Optimization: Oversee the deployment of high-performance computing clusters, ensuring 99.99% uptime and minimal latency.
- Stakeholder Communication: Translate complex technical concepts for executive stakeholders and collaborate with product teams to deliver cutting-edge solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Physics, Applied Mathematics, or a related field with a focus on Quantum Computing.
- Experience: Minimum 8 years of experience in software engineering, with at least 3 years specifically in AI/ML or Quantum Computing environments.
- Technical Skills: Proficiency in Python, C++, and CUDA; hands-on experience with quantum programming frameworks such as Qiskit, Cirq, or PyQuil.
- Architecture: Strong understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and edge computing paradigms.
- Problem Solving: Demonstrated ability to troubleshoot complex hardware-software integration issues and optimize performance under extreme constraints.
- Leadership: Proven track record of leading engineering teams through the full software development lifecycle.