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2026 AI Systems Architect

QuantumLeap Technologies
Austin
Estimated Salary
USD 150.000 – USD 220.000
New
Live Update
22 Mei 2026
Deadline
22 Mei 2027

Job Description

Shape the future of artificial intelligence as our lead architect for next-generation systems. QuantumLeap Technologies seeks a visionary 2026 AI Systems Architect to design scalable, ethical AI frameworks that will redefine industry standards over the next decade. Join our cross-disciplinary team at the forefront of quantum computing, neural networks, and autonomous decision-making systems.

Position includes hybrid work arrangements, competitive equity packages, and dedicated R&D budgets for experimental projects. Collaborate with Nobel laureates and industry pioneers to build AI solutions for climate modeling, personalized medicine, and sustainable energy systems.

Responsibilities

  • Architect quantum-resistant AI frameworks for 2026 deployment
  • Lead cross-functional teams in developing ethical AI governance protocols
  • Design neural networks capable of autonomous learning and adaptation
  • Integrate multi-modal data streams from IoT, biometric, and satellite networks
  • Develop AI safety protocols aligned with emerging global regulatory frameworks
  • Present strategic roadmaps to C-suite and board stakeholders
  • Research and prototype cutting-edge AI paradigms (e.g., neuromorphic computing)

Qualifications

  • PhD in Computer Science, AI, or Quantum Computing with 5+ years industry experience
  • Published research in Nature/Science on neural network optimization
  • Expertise in Python, TensorFlow, and quantum programming languages
  • Proven track record of deploying enterprise-scale AI systems (>10M users)
  • Deep understanding of ethical AI frameworks and bias mitigation
  • Experience with distributed computing architectures (Kubernetes, Spark)
  • Certification in AI governance frameworks (e.g., IEEE 7000)
  • Portfolio of open-source AI projects with 5K+ GitHub stars

Required Skills

AI Architecture Quantum Computing Neural Networks Ethics TensorFlow Python Kubernetes Research Leadership

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