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AI Systems Architect 2026

QuantumLeap Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
7 Juli 2026
Deadline
7 Jul 2027

Job Description

Join QuantumLeap Technologies as an AI Systems Architect to engineer the next generation of autonomous solutions for 2026. We're seeking a visionary leader to design scalable AI frameworks that will transform industries through quantum-enhanced machine learning and neural-semantic integration. This role offers unparalleled opportunity to shape humanity's technological future while working with Nobel Prize-winning researchers in our state-of-the-art Innovation Lab.

Our ideal candidate thrives at the intersection of theoretical computer science and practical implementation, with a passion for developing ethical AI systems that augment human capabilities. You'll lead cross-functional teams in building distributed neural networks capable of real-time predictive analytics across terabyte-scale datasets.

Responsibilities

  • Architect quantum-resistant AI systems processing 10+ petabytes daily
  • Design federated learning frameworks for multi-cloud deployment
  • Develop neural-semantic processors achieving human-level reasoning
  • Lead implementation of self-healing network topologies
  • Create ethical AI governance frameworks compliant with 2026 regulations
  • Optimize energy-efficient AI operations reducing carbon footprint by 40%
  • Mentor junior engineers in cutting-edge AI methodologies

Qualifications

  • PhD in Computer Science/AI with 8+ years industry experience
  • Published research in quantum machine learning or neural networks
  • Expertise in TensorFlow/PyTorch at petabyte scale
  • Proven track record of deploying production-grade AI systems
  • Deep knowledge of quantum computing principles (Qiskit experience required)
  • Certification in AI Ethics from IEEE or ACM
  • Experience with neuromorphic computing hardware

Required Skills

Quantum Computing Neural Networks Federated Learning AI Ethics TensorFlow PyTorch Qiskit Distributed Systems

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