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Information Technology 🏢 Full Time ⭐️ Verified

AI Innovation Architect 2026

QuantumLeap Systems
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
20 Mei 2026
Deadline
20 Mei 2027

Job Description

Join QuantumLeap Systems at the forefront of technological evolution. We're seeking an AI Innovation Architect to design and implement next-generation solutions that will redefine industries by 2026. This role combines strategic foresight with hands-on technical leadership to transform emerging AI capabilities into tangible business value. You'll collaborate with world-class researchers, engineers, and Fortune 500 partners to pioneer breakthrough applications in quantum computing, neural interfaces, and autonomous systems.

Our San Francisco hub offers unparalleled resources including a $50M R&D lab, startup incubator partnerships, and direct access to Silicon Valley's innovation ecosystem. We provide comprehensive benefits including equity, wellness stipends, and flexible work arrangements for top-tier talent.

Responsibilities

  • Architect AI/ML roadmaps targeting 2026 market disruption across healthcare, climate tech, and autonomous systems
  • Lead cross-functional teams to prototype and deploy generative AI solutions with <10% error margins
  • Establish strategic partnerships with quantum computing and neuromorphic hardware providers
  • Develop ethical AI governance frameworks for autonomous decision-making systems
  • Drive innovation sprints to integrate real-time data fusion from IoT and satellite networks
  • Present breakthrough concepts to C-suite executives and industry consortiums

Qualifications

  • 10+ years in AI/ML architecture with proven 2020-2025 implementation track record
  • Expertise in transformer architectures, quantum machine learning, and edge AI deployment
  • PhD or equivalent in Computer Science, Robotics, or related quantitative field
  • Published research in top-tier venues (NeurIPS, ICML, Nature AI) or equivalent industry impact
  • Experience leading teams of 15+ engineers in agile/scrum environments
  • Strong portfolio demonstrating end-to-end AI system lifecycle management
  • Certifications in AWS/Azure AI or equivalent cloud-native AI platforms

Required Skills

AI Architecture Quantum Computing Neural Networks Generative AI Strategic Foresight Machine Learning Cloud AI Autonomous Systems Ethics in AI Data Fusion

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