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2026 Futurist Lead

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

Job Description

Join Horizon Dynamics at the forefront of tomorrow. We're seeking visionary 2026 Futurist Leads to architect the next wave of human-machine evolution. This role demands strategic foresight, interdisciplinary mastery, and the ability to translate speculative innovation into actionable frameworks. You'll collaborate with quantum computing architects, neuro-interface designers, and synthetic biologists to redefine human potential in the post-quantum era.

Our San Francisco hub operates at the intersection of Silicon Valley's legacy and the bleeding edge of emerging tech. We offer equity, unlimited learning stipends, and a culture where 'impossible' is just a starting point.

Responsibilities

  • Lead cross-disciplinary R&D initiatives for 2026+ human augmentation technologies
  • Develop strategic roadmaps for quantum-AI convergence and neural symbiosis
  • Partner with governments to shape ethical frameworks for post-scarcity economies
  • Architect decentralized governance models for AI-driven autonomous systems
  • Conduct horizon-scanning across biotech, nanotech, and consciousness studies
  • Mentor next-generation futurists through our Quantum Leap Academy
  • Publish whitepapers on exponential tech's societal impact

Qualifications

  • PhD or equivalent in Futures Studies, Systems Theory, or Quantum Physics
  • 5+ years in strategic foresight with Fortune 500 or hypergrowth startups
  • Published work on singularity economics or post-human ethics
  • Proficiency in predictive modeling tools (e.g., GPT-4, Metaculus)
  • Experience with DARPA/NASA-style innovation ecosystems
  • Portfolio demonstrating 2020+ technology predictions with 85%+ accuracy
  • Fluency in at least two technical languages (Python, R, Solidity)
  • Expertise in quantum-resistant cryptography and neural interface protocols

Required Skills

Foresight Strategy Quantum Computing Neural Interfaces Synthetic Biology Systems Thinking Ethical AI Exponential Tech Governance Modeling

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