Chief Technology Officer

Join Omnia as a Co-Founder & CTO to build the AI platform that will redefine enterprise human capital. We are an early-stage startup seeking a visionary leader (ETH/EPFL preferred) to architect our system and culture from scratch in return for significant founding equity.

Define and own the end-to-end AI strategic vision and technical roadmap, ensuring tight alignment with Omnia’s mission, business goals, and user needs.

• Drive Innovation: Translate business objectives into concrete, scalable, AI-powered platform capabilities. Drive our competitive edge through continuous R&D into emerging technologies, tools, and methodologies.
• Build a World-Class Culture: Lead and mentor the engineering and AI/ML organisation, fostering a culture of excellence, innovation, continuous improvement, and knowledge sharing.
• Align Stakeholders: Serve as the key technical voice, translating complex concepts and roadmaps for executives, product managers, and external partners (research institutions, thought leaders).

Design, build, and continuously refine Omnia’s cloud-native technical architecture (AWS/GCP/Azure), ensuring it is modular, secure, and highly scalable.

• Drive Technology Selection: Lead the selection and oversight of the entire technology stack, choosing optimal frameworks, tools, and infrastructure for rapid development and robust deployment.
• Implement DevOps Excellence: Architect and oversee a modern DevOps strategy, including automated CI/CD pipelines, real-time monitoring, and cost-optimised infrastructure management to guarantee reliability, performance, and availability.
• Unify the System: Lead the seamless integration of AI models, data pipelines, and APIs into a single, cohesive, and high-performance product.

Guide the entire lifecycle of model development, from defining data strategies (sourcing, preprocessing, labelling) to building, testing, and deploying production-ready models.

• Champion MLOps Best Practices: Implement and enforce state-of-the-art MLOps practices, including CI/CD for machine learning, automated monitoring, model versioning, and retraining pipelines.
• Ensure Model Performance: Establish and own the frameworks for rigorous benchmarking, evaluation, and continuous monitoring of AI model performance, accuracy, and real-world business impact.

Define and own the data compliance and governance framework, ensuring the platform adheres strictly to GDPR, HIPAA, applicable data regulations, and data ethics principles.

• Embed Security by Design: Embed robust security principles across the platform, including end-to-end encryption, identity and access management (IAM), and secure API development.
• Mitigate Risks Proactively: Identify and mitigate risks related to both AI usage (e.g., bias, fairness, explainability) and system performance (e.g., cybersecurity resilience, stability, downtime).

• Demonstrated success defining AI/ML strategy and architecting complex, cloud-native systems from the ground up.
• A proven track record of translating high-level business goals into robust software architecture and scalable technical roadmaps.
• Experience designing and implementing bespoke machine learning frameworks that serve as the foundation for an intelligent, data-driven product.
• Expert-level command of a relevant tech stack for AI-driven applications (e.g., Python, Java, C++) and deep familiarity with major cloud platforms (AWS, GCP, Azure).
• Hands-on expertise in implementing modern MLOps pipelines for the continuous integration, delivery, monitoring, and retraining of machine learning models.
• Deep, practical knowledge of AI governance, performance evaluation frameworks, and risk mitigation strategies for production AI systems.
• Exceptional leadership and communication skills, with the ability to mentor a high-performing, cross-functional team and articulate a clear technical vision to all stakeholders.
• Proven experience leading technical teams in a fast-paced, agile startup or innovation-driven environment, with a relentless focus on execution and quality.
• A strategic mindset, with the ability to balance long-term technical debt, innovation, and immediate business priorities effectively.
• A firm grasp of Ethical AI principles and a deep understanding of data governance, security best practices, and compliance requirements, particularly in regulated environments (GDPR, HIPAA).