Backend Engineer, Health Data Platform (AI‑Augmented)

Clinical ink; Søborg; Hybrid; DKK 600,000 - 800,000; Full time

Job summary

Clinical Ink is seeking a Backend Engineer to join the Disease Management team in Denmark and the United States. You will build backend features in our Python stack, create robust tests, and ensure quality controls in a regulated environment.

You will learn to leverage AI coding agents while maintaining strong security and privacy standards. Collaborating across offices, you’ll contribute to data integrations with wearables and clinical data sources, instrument observability, and ensure

Qualifications

• Strong fundamentals in programming with eagerness to learn.
• Experience with APIs, databases, and version control; comfortable with testing.
• Driven to build and ship, curious learner.
• Open to AI-augmented development with verification mindset.
• Exposure to healthcare data or regulated software preferred.

Responsibilities

• Implement backend features in the Python stack across services.
• Write meaningful tests and ensure quality controls pass.
• Integrate wearables and clinical data sources under guidance.
• Instrument code with metrics and logs; learn production tooling.
• Respect PHI handling and least-privilege in development.
• Use AI coding agents effectively and verify outputs.
• Communicate clearly in code, PRs, and updates.

Skills

Python fundamentals

APIs & SQL

Version control

Testing & design

AI-assisted development

FastAPI / SQLAlchemy

AWS experience

Healthcare data (FHIR)

Regulated software

Tools

CloudWatch

Sentry

PostgreSQL

SQLAlchemy

Git

FastAPI

Job description

Clinical Ink is seeking a Backend Engineer to join the Disease Management team in Denmark and the United States. You will build backend features in our Python stack, create robust tests, and ensure quality controls in a regulated environment.

You will learn to leverage AI coding agents while maintaining strong security and privacy standards. Collaborating across offices, you’ll contribute to data integrations with wearables and clinical data sources, instrument observability, and ensure