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AI Futurist Strategist

Horizon Dynamics Inc.
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
1 Juli 2026
Deadline
1 Jul 2027

Job Description

Join our elite team at Horizon Dynamics as we architect the future of human-AI collaboration. We're seeking a visionary AI Futurist Strategist to pioneer breakthrough solutions for 2026 and beyond. In this pivotal role, you'll design transformative AI frameworks that redefine industry standards and drive exponential growth.

Our cutting-edge research lab operates at the intersection of quantum computing, neuromorphic engineering, and predictive analytics. You'll collaborate with Nobel laureates and industry disruptors to develop autonomous ethical AI systems that solve humanity's most complex challenges.

Responsibilities

  • Architect next-gen AI roadmaps for 2026+ technological adoption
  • Lead cross-functional teams in developing ethical AI governance frameworks
  • Conduct frontier research in emergent AI paradigms (AGI, sentient systems)
  • Design predictive models for AI-human symbiosis in 2030+ scenarios
  • Present strategic AI insights to C-suite executives and global policymakers
  • Drive innovation in quantum-AI integration and neuro-symbolic computing
  • Mentor AI ethics committees on responsible development protocols

Qualifications

  • PhD in AI, Cognitive Science, or related field with 5+ years research experience
  • Published work in top-tier AI journals (NeurIPS, ICML, Nature AI)
  • Expertise in federated learning, explainable AI, and adversarial robustness
  • Deep understanding of 2026+ AI regulatory landscapes and ethical frameworks
  • Proven track record of translating AI theory into commercial solutions
  • Experience with quantum computing architectures and neuromorphic hardware
  • Certification in AI Ethics from recognized institutions (e.g., IEEE, ACM)

Required Skills

AI Strategy Quantum Computing Neuromorphic Engineering Predictive Analytics Ethical AI Governance Federated Learning Explainable AI Quantum Machine Learning

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