Software Architect & Technical Lead
Role details
Job location
Tech stack
Job description
On behalf of our innovative medtech client we are looking for a hands-on senior technical leader to drive the architecture and evolution of a cloud-native SaaS platform that integrates machine learning and scientific modeling. This role combines software engineering excellence, scalable system design, and customer-facing technical leadership. You will define the technical roadmap, guide infrastructure decisions, and ensure the platform meets enterprise-grade standards for performance, security, and scalability., * Software Architecture & System Integration & Platform: Design and evolve a robust SaaS architecture, including microservices, cloud infrastructure, and DevOps pipelines.
- Hands-On Development: Contribute to coding, prototyping, and code reviews to maintain technical depth.
- Data Engineering: Implement secure, automated data pipelines for ingestion, transformation, and validation.
- Cross-Functional Collaboration: Work closely with scientific and ML teams to translate complex models into scalable software components.
- Customer Engagement: Act as a trusted technical advisor for enterprise clients, guiding integrations and secure data workflows.
- Team Leadership: Mentor developers, enforce best practices, and foster a culture of technical excellence.
Requirements
*Applicants must hold a valid EU work permit and/or reside within Europe. Please note that only eligible candidates will be contacted., * Strong experience in Python and modern software engineering principles.
- Proven track record in cloud architecture (AWS, Azure, or similar) and DevOps (CI/CD, Infrastructure-as-Code).
- Expertise in ML frameworks (TensorFlow, PyTorch, Scikit-learn) and understanding of MLOps principles.
- Knowledge of data pipeline design, APIs, and integration frameworks.
- Excellent communication skills for both technical and non-technical stakeholders.
Preferred
- Background in life sciences, biotech, or AI-driven SaaS platforms.
- Experience with hybrid modeling or scientific computing workflows.
- Familiarity with startup or scale-up environments.