Full Stack Developer

• Build the integration layer for AI solutions
• Develop services and APIs that enable ML models to be deployed and consumed within the platform
• Translate data science outputs into production-ready components
• Full stack application development
• Implement frontend and backend components for new platform capabilities
• Ensure clean integration between UI, services, and underlying data pipelines
• Collaborate across teams
• Work closely with data scientists, architects, and product stakeholders
• Help shape how RBQM analytics are exposed and used in practice
• Contribute to a scalable MVP
• Build with pragmatism: balancing speed (MVP) with maintainability
• Improve performance, stability and usability over time
• Support DevOps / deployment workflows
• Contribute to CI/CD pipelines and cloud-based deployments
• Help ensure services are robust and production-ready

• Solid experience in full stack development (typically ~3-6 years)
• Strong skills in:
• Backend development with C# .Net
• Frontend development Angular
• Exposure to AWS PaaS
• Containerization (Kubernetes and AWS EKS)
• Version control, CI/CD workflows and DevOps practices
• Experience in PostgreSQL
• Experience in building and consuming REST APIs
• Understanding of microservices or service-oriented architectures
• Ability to work independently in a fast-moving, somewhat ambiguous MVP environment

Nice to have (not required)

• Basic understanding of MLOps concepts (e.g., model deployment, APIs for inference)
• Experience in data-heavy applications or analytics platforms
• Knowledge in Messaging Middleware like RabittMQ
• Any background in healthcare, life sciences, or regulated environments

This role sits at a very practical and impactful intersection: you won’t build AI models-but you will make them usable in the real world.

We are developing an MVP on our platform (NXT) to onboard AI-driven RBQM (Risk-Based Quality Management) solutions in cardiology. These solutions are created by data scientists and domain experts but without the right engineering layer, they never reach end users.

That is where you come in.

You will help build the “last mile” between machine learning and clinical application, turning models into reliable, scalable and usable products that support clinical trial teams in making better decisions.

What We Offer

• Competitive compensation
• Attractive benefits (security, flexibility, support and well-being)
• Remote or hybrid working