Description
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 hands-on software development experience, with deep expertise in software architecture, system design, and technical execution.
- 3+ years of experience leading multidisciplinary R&D teams across Software Engineering, Product, and Data Science.
- Proven experience building and scaling cloud-based SaaS products using Python, JavaScript/TypeScript, Node.js, React, Docker, Kubernetes, and major cloud platforms.
- Advanced hands-on experience with AI coding tools (Cursor, Claude Code, or Codex) and AI-native engineering workflows, including development, debugging, code review, and automation.
- Strong knowledge of distributed systems, relational and NoSQL databases, CI/CD, and GitOps, including GitLab CI and Argo CD.
- Ability to lead from the front through direct involvement in architecture, coding, prototyping, code reviews, troubleshooting, and critical engineering initiatives.
- Strong communication and execution skills, with fluent English.
Preferred Qualifications
- Experience with production AI/ML systems, model serving, inference pipelines, MLOps, data platforms, or high-scale, data-intensive environments.
- Background in healthcare, biotechnology, 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.
