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Future Tech Strategist

Innovate Tomorrow Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
16 Mei 2026
Deadline
16 Mei 2027

Job Description

Join Innovate Tomorrow Labs at the forefront of technological evolution. We're seeking a visionary Future Tech Strategist to architect solutions for 2026 and beyond. You'll lead cross-functional teams to develop groundbreaking AI, quantum computing, and biotech integrations that redefine industries. This role demands a blend of technical acumen and strategic foresight to transform emerging concepts into market-ready innovations.

Our dynamic startup environment offers unparalleled opportunities to shape the future while working alongside world-class researchers and engineers. If you thrive at the intersection of science, business, and human potential, this is your calling.

Responsibilities

  • Develop 5-year technology roadmaps aligned with market trends and business objectives
  • Lead R&D initiatives in AI ethics, quantum algorithms, and sustainable tech
  • Collaborate with C-suite executives to integrate future tech into corporate strategy
  • Manage innovation budgets and vendor partnerships for emerging technologies
  • Present strategic frameworks to stakeholders and investors
  • Anticipate disruptive technologies and mitigate implementation risks
  • Mentor technical teams in futuristic development methodologies

Qualifications

  • Master's degree in Computer Science, Engineering, or related field
  • 8+ years in tech strategy with 3+ years in emerging technologies
  • Proven track record in AI, quantum, or biotech innovation
  • Exceptional data modeling and scenario planning capabilities
  • Certification in Futurism or Technology Foresight preferred
  • Experience scaling tech startups from concept to IPO
  • Strong analytical skills with ability to visualize complex systems
  • Published research in peer-reviewed tech journals

Required Skills

AI Strategy Quantum Computing Biotech Integration Technology Roadmapping Futurism Innovation Management Systems Thinking Data Modeling

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