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2026 AI Infrastructure Architect

QuantumLeap Solutions
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Shape the future of AI infrastructure at QuantumLeap Solutions. We're seeking a visionary 2026 AI Infrastructure Architect to design and implement next-generation computing frameworks that will power the next wave of artificial intelligence breakthroughs. Join our elite team at the intersection of quantum computing, edge AI, and neural network optimization to build scalable, secure, and hyper-efficient systems that will define the technological landscape of 2026 and beyond.

This role offers unparalleled opportunities to pioneer sustainable AI infrastructure, collaborate with Nobel Prize-winning researchers, and directly influence how enterprises leverage artificial intelligence for global impact. Your work will enable breakthroughs in climate modeling, personalized medicine, and autonomous systems while setting new industry standards for ethical AI deployment.

Responsibilities

  • Architect quantum-resistant AI infrastructure supporting exascale computing requirements
  • Design edge-to-cloud neural network pipelines with sub-5ms latency
  • Lead implementation of federated learning frameworks for privacy-preserving AI
  • Develop zero-trust security protocols for AI model deployment and data pipelines
  • Optimize carbon-neutral computing architectures for large-scale AI training
  • Collaborate with quantum computing teams to hybridize classical-quantum ML workflows
  • Create predictive scaling systems for dynamic AI resource allocation

Qualifications

  • 10+ years in distributed systems architecture with AI/ML infrastructure specialization
  • Expertise in Kubernetes, TensorFlow Extended, and high-performance computing clusters
  • Proven experience with quantum computing interfaces (Qiskit, Cirq, or similar)
  • Certified in Google Cloud/AWS/Azure AI infrastructure or equivalent
  • Published research in neural network optimization or quantum machine learning
  • Demonstrated success in building carbon-efficient computing solutions
  • PhD in Computer Science, Quantum Physics, or related field preferred
  • Fluency in Python, Rust, and low-level system programming

Required Skills

Quantum Computing Distributed Systems Kubernetes TensorFlow Extended Qiskit Zero-Trust Security Federated Learning Edge AI Carbon-Neutral Computing Neural Network Optimization

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