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Lead Quantum AI Architect (2026 Initiative)

OmniFuture Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Are you ready to define the landscape of computing for the year 2026? OmniFuture Technologies is building the next generation of Artificial General Intelligence (AGI) and we need a visionary Lead Quantum Architect to lead our Q-2026 Roadmap.

In this pivotal role, you will bridge the gap between classical machine learning and quantum supremacy. You will design the architectural frameworks that prepare our models for the massive computational shifts anticipated by 2026, ensuring our systems are scalable, secure, and future-proof.

Why Join Us?

  • Work on cutting-edge research that defines the future of tech.
  • Competitive equity package and health benefits.
  • Flexible remote-first culture with a hub in San Francisco.

Responsibilities

  • Architect Quantum-Ready Systems: Design and implement scalable quantum computing architectures optimized for NISQ (Noisy Intermediate-Scale Quantum) devices.
  • Q-2026 Roadmap Planning: Lead the technical strategy for integrating quantum algorithms into our core AI infrastructure by the target year of 2026.
  • Model Optimization: Develop hybrid classical-quantum models that outperform traditional GPUs in specific computational domains.
  • Team Leadership: Mentor a team of brilliant engineers and data scientists, fostering a culture of innovation and technical excellence.
  • R&D Collaboration: Partner with academic institutions and research labs to stay ahead of quantum hardware advancements.
  • Security & Compliance: Implement robust security protocols for quantum-resistant cryptography and data protection.

Qualifications

  • Education: PhD or Master’s degree in Computer Science, Physics, Mathematics, or a related field with a focus on Quantum Information.
  • Experience: 7+ years of experience in software architecture, with at least 3 years specifically in quantum computing or AI research.
  • Technical Skills: Proficiency in Python, C++, and quantum programming languages (Qiskit, Cirq, or Project Q).
  • Frameworks: Deep understanding of classical ML frameworks (TensorFlow, PyTorch) and how to integrate them with quantum backends.
  • Problem Solving: Proven track record of solving complex, high-level technical challenges in distributed systems.
  • Communication: Exceptional ability to translate complex quantum concepts for diverse stakeholders and cross-functional teams.

Required Skills

Quantum Computing Machine Learning Python C++ Qiskit Cirq TensorFlow Distributed Systems Cloud Architecture NISQ Research

Ready to Take This Challenge?

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