Software engineer (platform and clinical integrations)

The Swiss Biotech Association seeks a mid-level Software Engineer to build and maintain the core infrastructure and clinical integration layer for an AI diagnostics platform in Basel.

This high-ownership position focuses on deploying, operating, and ensuring the trustworthiness of AI systems within clinical environments. The engineer will be responsible for architecting the foundational infrastructure and the clinical integration layer of the platform.

Responsibilities

• Architect and maintain scalable cloud infrastructure using Infrastructure-as-Code
• Design and operate CI/CD systems for safe, auditable deployments across environments
• Build backend services and APIs supporting clinical workflows and platform functionality
• Develop integrations with Laboratory Information Systems (LIS) using healthcare standards (HL7 / FHIR)
• Build internal tools and lightweight frontend applications for clinical and operational users
• Implement security, observability, and compliance controls (ISO 27001, HIPAA, GDPR) across an international network of laboratories
• Ensure system reliability, auditability, and traceability across all platform components

Requirements

• 4+ years in Platform Engineering, SWE, or Infrastructure roles
• Strong experience with cloud infrastructure (AWS or GCP) and Kubernetes
• Proven experience with Infrastructure-as-Code (Terraform, Pulumi, or similar)
• Experience building production backend systems (Python, Go, Java, etc.) and frontends (React / TypeScript)
• Experience with CI/CD, observability, and distributed systems
• Background in regulated or high-reliability environments (healthcare, fintech, SaMD)
• Work permit valid in Switzerland or EU

Nice to have

• Experience with LIS integration or healthcare interoperability (HL7 / FHIR / DICOM)
• Experience building systems with auditability or regulatory constraints
• Exposure to clinical or diagnostic workflows

About the company

The company is transforming clinical diagnostics by extracting genomic information from routine microscopic imaging. The company's goal is to make diagnostics faster, more scalable, and more accessible. The team works at the intersection of machine learning, medical imaging, and clinical infrastructure.

• The company is transforming clinical diagnostics by extracting genomic information from routine microscopic imaging.
• The company's goal is to make diagnostics faster, more scalable, and more accessible.
• The team works at the intersection of machine learning, medical imaging, and clinical infrastructure.