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2026 AI Integration Architect

QuantumLeap Dynamics
San Francisco
Estimated Salary
USD 150.000 – USD 220.000
New
Live Update
1 Juli 2026
Deadline
1 Jul 2027

Job Description

Join QuantumLeap Dynamics at the forefront of technological evolution. We're seeking a visionary 2026 AI Integration Architect to architect the next generation of intelligent systems that will redefine industries. This role demands a blend of strategic foresight, technical mastery, and innovative thinking to bridge emerging AI capabilities with real-world applications. You'll lead transformative projects in quantum-adjacent computing, neuro-symbolic AI, and autonomous system orchestration while mentoring cross-functional teams to deliver breakthrough solutions.

Why QuantumLeap? We're not just building for today – we're engineering the future. Our state-of-the-art R&D center in San Francisco offers unparalleled resources to pioneer solutions that will shape the technological landscape of 2026 and beyond.

Responsibilities

  • Design and implement AI integration frameworks for quantum-classical hybrid systems
  • Lead research initiatives in explainable AI and ethical autonomous decision-making
  • Develop neural-symbolic architectures for next-gen human-AI collaboration
  • Architect distributed AI systems with zero-trust security paradigms
  • Partner with quantum computing teams to optimize AI-algorithm performance
  • Create predictive models for technological adoption in 2026+ ecosystems
  • Mentor junior engineers in emerging AI paradigms and integration methodologies

Qualifications

  • MS/PhD in Computer Science, AI, or related field with 8+ years experience
  • Expertise in transformer architectures, quantum machine learning, and neuro-symbolic systems
  • Proven track record architecting AI systems for enterprise-scale deployment
  • Deep understanding of ethical AI frameworks and regulatory compliance (EU AI Act, NIST AI RMF)
  • Proficiency in Python, TensorFlow/PyTorch, and quantum programming languages (Q#, Qiskit)
  • Experience with distributed computing frameworks (Kubernetes, Apache Spark)
  • Published research in top-tier AI/ML conferences or journals

Required Skills

AI Integration Quantum Computing Neural-Symbolic AI Ethical AI System Architecture TensorFlow PyTorch Qiskit Kubernetes Explainable AI

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