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Information Technology 🏢 Full Time ⭐️ Verified

AI Futurist Strategist - 2026 Vision

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

Job Description

Join Horizon Dynamics at the forefront of tomorrow's technological landscape. We're seeking an AI Futurist Strategist to architect 2026's digital frontier, shaping how humanity interacts with emerging technologies. This role blends cutting-edge AI research with visionary business strategy, requiring both technical prowess and philosophical foresight.

As a key architect of our 2026 roadmap, you'll collaborate with quantum computing pioneers, neuro-interface developers, and climate AI architects to build sustainable, human-centric solutions. Your work will directly influence how Fortune 500 companies navigate the ethical and operational challenges of the coming decade.

Responsibilities

  • Architect AI-driven strategic roadmaps for 2026-2030 technology adoption
  • Lead cross-functional R&D initiatives in generative AI and neural interfaces
  • Develop ethical frameworks for autonomous systems and quantum applications
  • Partner with C-suite executives to future-proof enterprise ecosystems
  • Produce white papers and thought leadership on emerging tech paradigms
  • Oversee prototype development of next-gen human-machine interfaces
  • Guide policy recommendations for AI governance in critical infrastructure

Qualifications

  • PhD in Computer Science, Cognitive Science, or related field
  • 5+ years in AI research with publications at NeurIPS/ICML
  • Proven experience in strategic technology forecasting
  • Expertise in quantum machine learning and neuro-symbolic AI
  • Deep understanding of ethical AI frameworks and regulatory landscapes
  • Portfolio of deployed AI systems impacting 100K+ users
  • Certification in AI governance (e.g., IEEE Ethically Aligned Design)

Required Skills

Artificial Intelligence Strategic Planning Quantum Computing Neural Interfaces Ethical AI Technology Forecasting Machine Learning Policy Development

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