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AI Futurist Strategist

Horizon Dynamics Corp
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

Shape tomorrow's technology landscape as a pioneering AI Futurist Strategist at Horizon Dynamics Corp. We're seeking visionary minds to architect the digital frontier of 2026 and beyond. Join our elite team in redefining human-machine collaboration, ethical AI governance, and autonomous system integration. This isn't just a roleβ€”it's your chance to sculpt the future of intelligent technology.

As a cornerstone of our Innovation Nexus division, you'll influence breakthrough projects in quantum computing interfaces, neural-semantic AI, and predictive human augmentation. We offer unparalleled resources, collaborative freedom, and the opportunity to publish groundbreaking research in partnership with MIT and Stanford's future-tech initiatives.

Responsibilities

  • Architect 2026+ AI roadmaps integrating quantum computing and neural networks
  • Develop ethical frameworks for autonomous decision-making systems
  • Lead cross-functional teams in prototyping next-gen human-AI interfaces
  • Partner with academic institutions on future-tech research initiatives
  • Strategize market disruption through predictive AI modeling
  • Present visionary concepts to C-suite and industry consortiums
  • Guide policy development for emerging AI regulatory landscapes

Qualifications

  • PhD in Computer Science, Cognitive Science, or Futurism (or equivalent experience)
  • 5+ years in AI strategy with published research in top-tier journals
  • Expertise in quantum computing architectures and neural-symbolic AI
  • Proven track record of scaling AI systems to enterprise level
  • Deep understanding of AI ethics and regulatory frameworks
  • Exceptional communication skills for complex technical storytelling
  • Portfolio of 2025+ technology foresight projects or publications

Required Skills

AI Strategy Quantum Computing Neural Networks Futurism Ethics Predictive Modeling Neural Interfaces

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