Careers at Corsano Health

Corsano Health is seeking a hands-on Delivery & Validation Lead to strengthen execution discipline, testing control, and release predictability across our connected digital health platform. This critical leadership role combines software delivery management with structured validation in a fast-moving, regulated MedTech environment.

In this role, you will own the software delivery workflow across cloud, portal, mobile applications, and firmware-dependent components, ensuring that every software release is backed by rigorous testing evidence and full regulatory compliance.

Key Responsibilities

• Own the comprehensive validation approach across component, integration, system, regression, and release testing activities.
• Drive weekly sprint and milestone follow-up across engineering teams with full visibility on owners, deadlines, blockers, and dependencies.
• Coordinate software delivery across cloud backend, web portal, mobile apps, and firmware workstreams to maintain release readiness.
• Track defects, retesting verification, unresolved issues, and residual risks, supporting go/no-go release decisions with factual status dashboards.
• Contribute to automated testing frameworks, CI/CD pipelines, and infrastructure-as-code validation setups.
• Collaborate with Quality & Regulatory teams to ensure complete traceability, design control, and compliance with EU Medical Device Regulation (CE-MDR) and US FDA 21 CFR Part 820 requirements.

Required Experience & Qualifications

• 7–10 years of experience in software delivery, software validation, technical program management, or quality engineering leadership.
• Proven expertise coordinating complex releases across distributed technical domains including cloud, web portals, mobile apps, and embedded firmware.
• Hands-on experience with integration testing, defect tracking, CI/CD automated validation, and release governance in medical devices, digital health, or quality-critical industries.
• Practical knowledge of Agile/Scrum development combined with structured release discipline and regulatory documentation standards.

Join our mobile engineering team in Geneva to evolve our core Bluetooth Low Energy (BLE 5.0) streaming engine, Android client applications, and Mobile SDK. You will engineer highly robust code responsible for ingesting continuous vital biometrics—including heart rate, respiration rate, SpO2, skin temperature, and ECG rhythm strips—directly from the CardioWatch 287 medical bracelet.

Key Responsibilities

• Design, build, and maintain high-performance Kotlin applications and Mobile SDKs connected via BLE 5.0 to wearable biosensors.
• Implement secure local data persistence, RESTful API integration, and encrypted communication channels to our AWS cloud infrastructure.
• Write, review, and maintain comprehensive technical documentation aligned with IEC 62304 medical device software lifecycle standards.
• Design unit, integration, and system test suites to support regulatory verification and validation activities required under CE-MDR and FDA frameworks.
• Optimize real-time data streaming, memory usage, and background sync efficiency on mobile OS environments.

Required Experience & Qualifications

• Master's degree in Computer Science, Software Engineering, or equivalent practical experience.
• 2+ years of professional mobile development experience with proven hands-on expertise in Bluetooth Low Energy (BLE 5.0) protocols.
• Solid mastery of Kotlin, multi-threading asynchronous programming, local mobile datastores (e.g., Realm), and secure RESTful JSON APIs.
• Familiarity with ISO 27001 security controls, HIPAA/GDPR data protection by design, and medical software development processes is highly advantageous.

Corsano Health is expanding its cloud engineering team at The Hague Tech hub. We are looking for a dedicated Cloud Backend Developer to design, scale, and operate our AWS cloud platform, which ingests and processes continuous biometric streams from thousands of monitored hospital beds and ambulatory patients globally.

Key Responsibilities

• Design, implement, and operate microservices and RESTful APIs for high-frequency biometric data ingestion, storage, and EHR/EMR export.
• Manage cloud-native infrastructure on AWS utilizing services such as EC2, ECS/EKS, Lambda, S3, RDS, DynamoDB, and CloudWatch.
• Enforce strict security-by-design standards in alignment with ISO 27001, including IAM role segregation, end-to-end encryption, audit logging, and automated threat monitoring.
• Build near real-time data pipelines for automated Early Warning Score (EWS) calculations and clinical alarm notifications.
• Collaborate closely with firmware, mobile, data science, and clinical specialists to deliver end-to-end telemetry reliability.

Required Experience & Qualifications

• 3+ years of experience as a Backend or Cloud Engineer in data-intensive SaaS or healthcare environments.
• Proficiency in backend frameworks (e.g., PHP Laravel, Node.js, or Go) and relational database architectures (PostgreSQL/MySQL).
• Hands-on experience with containerization (Docker, ECS, or Kubernetes), infrastructure-as-code, and automated CI/CD deployment pipelines.
• Deep understanding of web security, API token management, and international privacy standards including GDPR and HIPAA.

Working directly under our clinical and data science leadership at our Yes!Delft office, the Data Scientist Intern will analyze raw multi-sensor physiological signals (PPG, single-lead ECG, accelerometer, skin temperature, GSR) at up to 128 Hz to refine algorithmic accuracy and develop automated anomaly detection models.

Key Responsibilities

• Extract, clean, and analyze high-resolution biosensor telemetry gathered across hospital wards and clinical trial cohorts.
• Develop and benchmark machine learning models for motion-artifact filtering, arrhythmia continuous detection, and physiological trend analysis.
• Assist in building automated anomaly detection systems and continuous signal quality verification pipelines.
• Document validation methodologies and present statistical findings clearly to cross-functional engineering and medical teams.

Required Experience & Qualifications

• Enrolled in or completed a BSc/MSc degree in Computer Science, Technical Medicine, Biomedical Engineering, or Applied Mathematics (e.g., TU Delft).
• Strong knowledge of machine learning methodologies, applied statistics, and statistical signal processing.
• Proficiency with data science toolkits (Python, R, NumPy, SciPy, MatLab) and relational/NoSQL datastores.
• Analytical mindset, structured documentation habits, and fluency in technical English.