Job Description
Join Horizon Innovations Group at the forefront of tomorrow's revolution. We're seeking a visionary 2026 Futurist Lead to architect the next decade's technological landscape. This pivotal role demands strategic foresight, cross-industry collaboration, and a relentless drive to transform abstract concepts into actionable innovation. You'll lead our flagship 'Project 2026' initiative, partnering with C-suite executives, R&D pioneers, and global thought leaders to shape industries before they exist. Our Austin headquarters offers an unparalleled ecosystem of emerging tech startups, academic research institutions, and venture capital networks.
What We Offer:
• Cutting-edge resources for prototyping and experimentation
• Equity package in our pre-IPO growth stage
• Flexible hybrid work with quarterly innovation retreats
• Comprehensive wellness and professional development stipend
Responsibilities
- Develop and implement 2026 strategic roadmaps for AI, biotech, and quantum computing convergence
- Lead cross-functional task forces to validate emerging technologies through market simulations
- Establish partnerships with academic institutions and government innovation labs
- Present annual 'State of 2026' briefings to board and investor stakeholders
- Mentor a cohort of futurist researchers and technology ethicists
- Author white papers on long-term societal impact of technological adoption
- Oversee $5M+ annual innovation fund allocation for speculative R&D
Qualifications
- 10+ years in strategic foresight, technology innovation, or venture capital
- Published thought leadership in future studies (peer-reviewed journals or major publications)
- Advanced degree in Futures Studies, Systems Engineering, or related field
- Proven track record of commercializing emerging technologies
- Deep expertise in at least two of: AI governance, synthetic biology, or quantum computing
- Certification in scenario planning and technology roadmapping
- Experience presenting to C-suite and government bodies
- Portfolio demonstrating successful prediction of tech adoption curves