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Information Technology 🏢 Full Time ⭐️ Verified

AI Futurist Strategist (2026 Vision)

Quantum Leap Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Join Quantum Leap Innovations at the forefront of tomorrow's technology landscape. As an AI Futurist Strategist (2026 Vision), you'll architect the next generation of intelligent systems that will redefine industries by 2026. We're seeking a visionary thinker to bridge cutting-edge AI research with practical business applications, driving innovation in autonomous systems, quantum computing integration, and human-AI symbiosis. This role offers unparalleled opportunities to shape the future while working with Nobel laureates and industry pioneers in our state-of-the-art San Francisco hub.

Responsibilities

  • Develop 2026 roadmaps for AI-powered autonomous systems in healthcare and logistics
  • Lead cross-functional teams in implementing quantum-resistant encryption protocols
  • Architect neural interfaces enabling seamless human-AI collaboration
  • Drive ethical AI frameworks for transparent decision-making systems
  • Conduct horizon scanning for emerging technologies impacting 2026 markets
  • Present strategic recommendations to C-suite and board members
  • Partner with academic institutions to accelerate AI breakthrough timelines

Qualifications

  • PhD in Computer Science, AI, or related field with 5+ years industry experience
  • Published research in top-tier AI/ML conferences (NeurIPS, ICML, etc.)
  • Expertise in generative AI, federated learning, and explainable AI
  • Proven track record of deploying AI systems at scale (>10M users)
  • Deep understanding of quantum computing principles and applications
  • Certification in AI ethics frameworks (IEEE, EU AI Act)
  • Experience with strategic technology roadmapping for 3-5 year horizons

Required Skills

Artificial Intelligence Machine Learning Quantum Computing Strategic Planning Neural Interfaces Ethical AI Generative AI Federated Learning

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