Head of R&D

About the Role

We are seeking a hands-on Head of R&D to lead our Software Engineering, Product, and Data Science teams. This role will be responsible for accelerating product delivery, strengthening technical execution, and ensuring alignment between our AI roadmap and customer-facing products.

This is a player-coach role, combining technical leadership, software architecture, team management, and execution ownership.

Responsibilities:

• Lead and manage multidisciplinary R&D teams across Software, Product, and Data Science.

• Own the execution of the company’s technology and product roadmap.

• Define and drive software architecture, scalability, reliability, and engineering best practices.

• Work closely with Product and AI teams to translate innovation into commercial products.

• Improve development workflows, team productivity, and delivery velocity.

• Remove technical and organizational bottlenecks.

• Mentor team leads and foster a culture of ownership, accountability, and excellence.

• Participate directly in architecture reviews and key technical decisions.

Requirements

• B.Sc. in Computer Science, Software Engineering, or a related field.

• 8+ years of software development experience.

• 3+ years managing multidisciplinary R&D teams.

• Strong hands-on software architecture and system design experience.

• Experience building and scaling cloud-based SaaS products.

• Proven ability to lead engineering teams while working closely with Product and AI/Data Science organizations.

• Strong technical leadership, communication, and execution skills.

• Fluent English.

Preferred Qualifications

• Experience in AI/ML-driven products and platforms.

• Experience with modern cloud infrastructure, MLOps, and data platforms.

• Background in healthcare, biotech, or life sciences.

• Experience scaling R&D organizations in fast-growing startups.

What Success Looks Like

• Faster and more predictable product delivery.

• Strong collaboration between Software, Product, and Data Science teams.

• Scalable engineering processes and architecture.

• Successful translation of AI capabilities into customer-facing products.

• A high-performing R&D organization aligned with business objectives.