POSTED Sep 17

Head of AI @ Olakai

at AI Fund

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Olakai is building the control plane for generative AI in the enterprise. Founded by Xavier Casanova (Founder and CEO of Liveclicker) and backed by Andrew Ng’s AI Fund and Dean Sysman (Founder and CEO of Axonious), Olakai gives CIOs the visibility, control, and secure tooling to confidently experiment with AI tools. As their company’s AI footprint grows, LocalNode evolves into the centralized AI platform, extending security, visibility, and auditing capabilities across all tools—whether built internally, by tech giants, or by the smallest startups.

What you’ll do: 

This Head of AI will be responsible for providing technical leadership and guidance across the Engineering team and AI product line.

Role Responsibilities:

  • Lead groundbreaking projects in AI
  • Build and manage a team of machine learning scientists and engineers
  • Collaborate with the founding engineering team to make pivotal decisions regarding infrastructure, architecture, and scalability
  • Work with the CEO and product team to incorporate their aims with the machine learning strategy and development
  • Work with other company leaders to decide on strategies and roadmaps
  • Maintain and scale existing technologies
  • Stay informed of the latest AI/ ML developments
  • ,

    Requirements:

  • A leader who thrives in the vibrant ecosystem of a startup
  • Bachelor's or Master's degree or Phd in Computer Science, Artificial Intelligence, Machine Learning or related field
  • 6 - 8+ years’ experience in AI/ML
  • Ability to articulate your vision and complex technology solutions with a broad audience, from product/design leaders to investors
  • Deep understanding of MLOps, including experience with CI/CD pipelines, model deployment, monitoring, and retraining strategies.
  • ,

    Nice to Have:

  • Proficiency in building and deploying AI agents, with hands-on experience using frameworks like LangChain or LlamaIndex
  • Solid understanding of LLMOps concepts, with knowledge of managing and optimizing large language models in production environments.
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