Full Stack Engineer (AI Platform / RBQM)

eResearchTechnology GmbH
Leuven, Belgium
23 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Business Analytics Applications C Sharp (Programming Language) Continuous Integration DevOps Middleware PostgreSQL Machine Learning Platform as a Service (PAAS) Service-Oriented Architecture
+12 more
Backend Containerization AI Platforms AngularJS Kubernetes Machine Learning Operations Front End Software Development Restful APIs Software Version Control Data Pipelines AWS EKS Microservices

Job description

  • 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

Requirements

  • 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

Benefits & conditions

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

About the company

At Clario, our purpose is to transform lives by unlocking better evidence. It’s a cause that unites and inspires us. It’s why we come to work-and how we empower our people to make a positive impact every day. Whether you’re advancing clinical science, building innovative technology, or supporting our global teams, your work helps bring life-changing therapies to patients faster.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on clarioclinical.wd1.myworkdayjobs.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:20 min

Identifying multi-disciplinary talent for developer experience engineering roles

Hazal Mestci +1 · Coffee With Developers

1:52 min

Structuring and scaling the backend engineering team

Stefan Lingler Stefan Lingler +1 · Coffee With Developers

3:49 min

Container hosting options available on Amazon Web Services

Federico Fregosi · World Congress 2022

2:17 min

Mapping the maturity roadmap for scaled devops adoption

Dominik Krichbaum Dominik Krichbaum · World Congress 2026 Europe

1:38 min

Transitioning into backend engineering from web development

Stefan Lingler Stefan Lingler +1 · Coffee With Developers

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

Videos

See all

Related articles

See all