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Information Technology 🏢 Full Time ⭐️ Verified

AI Systems Architect 2026

QuantumLeap Innovations
Austin
Estimated Salary
USD 180.000 – USD 250.000
Live Update
11 Mei 2026
Deadline
11 Mei 2027

Job Description

Join QuantumLeap Innovations at the forefront of technological evolution. We're seeking visionary AI Systems Architects to design next-generation autonomous frameworks for 2026 and beyond. This pivotal role bridges quantum computing, neural networks, and ethical AI deployment in high-stakes environments. You'll architect solutions that redefine industry standards while collaborating with Nobel laureates and NASA-affiliated researchers.

What you'll achieve:

  • Design scalable AI systems processing 10+ exabytes daily
  • Lead quantum machine learning integration initiatives
  • Develop ethical AI governance frameworks for autonomous systems
  • Architect neural-symbolic AI hybrids for explainable decision-making

Responsibilities

  • Architect quantum-resistant AI infrastructure for global enterprises
  • Design federated learning systems across 50+ data centers
  • Develop neural-symbolic AI frameworks for autonomous decision-making
  • Lead ethical AI governance implementation per 2026 regulatory standards
  • Optimize AI models for edge-to-cloud deployment
  • Collaborate with quantum computing researchers on hybrid systems
  • Mentor cross-functional teams in AI-first methodologies

Qualifications

  • PhD in Computer Science/AI with 8+ years experience
  • Published research in quantum machine learning or neural-symbolic systems
  • Expertise in federated learning frameworks (TensorFlow Federated, PySyft)
  • Proven track record architecting AI systems processing >1 petabyte daily
  • Deep understanding of 2026 AI regulatory landscapes (EU AI Act, US SAFE AI Act)
  • Proficiency in quantum programming (Qiskit, Cirq)
  • Experience deploying AI in regulated industries (healthcare, aerospace)

Required Skills

Quantum Computing Neural-Symbolic AI Federated Learning AI Governance Quantum Machine Learning TensorFlow PyTorch Explainable AI Edge Computing

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