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Software Development

Application Developer Medior

Location
Brussels, Belgium
Work mode
On-site
Contract
Contract · Mid
Closed
19 Jun 2026

This mission closed on 19 Jun 2026.

It stays online for reference, but it no longer takes applications.

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About the mission

We are looking for a hands-on Full Stack Developer to build and deploy scalable AI-powered applications. The ideal candidate will have experience in both frontend and backend development, with a strong focus on AI integration and collaboration with AI/ML engineers.

Read the full description

About the Role

We are seeking a hands-on Full Stack Developer to build and deploy scalable AI-powered applications that enhance user experiences and business operations. You will work at the intersection of frontend development, backend engineering, and AI integration, ensuring seamless, high-performance, and intelligent solutions. This role is ideal for a developer passionate about bridging the gap between traditional software engineering and cutting-edge AI technologies.

Key Responsibilities

Full Stack Development

Design, develop, and maintain end-to-end AI-driven applications, from responsive UIs to robust backend services.
Build RESTful APIs and microservices to integrate AI models (e.g., LLMs, RAG pipelines, or custom ML models) into production systems.
Implement real-time data processing and workflows to support AI features (e.g., chatbots, recommendation engines, or predictive analytics).
Optimize application performance, scalability, and security for high-traffic, AI-enabled platforms.

AI Integration & Collaboration

Work closely with AI/ML engineers to deploy and operationalize models (e.g., via APIs, SDKs, or embedded inference).
Develop user interfaces for AI-powered tools (e.g., dashboards, chat interfaces, or interactive visualizations).
Ensure seamless integration of AI features into existing applications, including fallback mechanisms and graceful degradation.
Collaborate with data scientists to refine model inputs/outputs and improve usability.

Infrastructure & DevOps

Deploy and manage cloud-based infrastructure (i.c., Azure) for AI applications, including containerization (Kubernetes) and CI/CD pipelines.
Implement monitoring, logging, and observability tools (e.g., Prometheus, Grafana, ELK) to track AI model performance and system health.
Optimize latency, cost, and reliability for AI workloads (e.g., model serving, vector databases, or batch processing).

User Experience & Testing

Design intuitive UIs for AI-driven features, prioritizing accessibility and usability.
Develop automated testing frameworks (unit, integration, E2E) for both frontend and backend components, including AI model validation.
Conduct A/B testing and gather user feedback to iterate on AI features.

Compliance & Governance

Ensure applications comply with data privacy regulations (e.g., GDPR) and security best practices.
Document APIs, architecture decisions, and AI integration workflows for cross-team collaboration.

Profile

Education:

Bachelor’s/Master’s in Computer Science, Software Engineering, or equivalent experience.

Experience:

3+ years in full stack development (frontend + backend).
Hands-on experience with AI/ML integration (e.g., calling LLM APIs, deploying models, or working with RAG systems).

Proficiency in modern frameworks:

Frontend: React
Backend: Python (FastAPI, Django, Flask), Node.js, or Java/Spring.
Databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis).
Cloud: Azure, AWS, or GCP (e.g., serverless, Kubernetes).
Familiarity with AI tools/libraries (e.g., LangChain, Hugging Face, TensorFlow Serving) is a plus.

Nice to Have:

Experience with vector databases (e.g., Elastic, chromaDB) or retrieval systems.
Knowledge of conversational AI (e.g., chatbots, voice assistants).
Background in financial services, healthcare, or regulated industries.

Soft Skills

Strong problem-solving and debugging skills.
Ability to collaborate with AI teams, designers, and product managers.
Ownership of features from development to production.
Clear communication and documentation skills.

What you'll do

  • Design, develop, and maintain end-to-end AI-driven applications, from responsive UIs to robust backend services.
  • Build RESTful APIs and microservices to integrate AI models (e.g., LLMs, RAG pipelines, or custom ML models) into production systems.
  • Implement real-time data processing and workflows to support AI features (e.g., chatbots, recommendation engines, or predictive analytics).
  • Optimize application performance, scalability, and security for high-traffic, AI-enabled platforms.
  • Work closely with AI/ML engineers to deploy and operationalize models (e.g., via APIs, SDKs, or embedded inference).
  • Develop user interfaces for AI-powered tools (e.g., dashboards, chat interfaces, or interactive visualizations).
  • Ensure seamless integration of AI features into existing applications, including fallback mechanisms and graceful degradation.
  • Collaborate with data scientists to refine model inputs/outputs and improve usability.
  • Deploy and manage cloud-based infrastructure (i.c., Azure) for AI applications, including containerization (Kubernetes) and CI/CD pipelines.
  • Implement monitoring, logging, and observability tools (e.g., Prometheus, Grafana, ELK) to track AI model performance and system health.
  • Optimize latency, cost, and reliability for AI workloads (e.g., model serving, vector databases, or batch processing).
  • Design intuitive UIs for AI-driven features, prioritizing accessibility and usability.
  • Develop automated testing frameworks (unit, integration, E2E) for both frontend and backend components, including AI model validation.
  • Conduct A/B testing and gather user feedback to iterate on AI features.
  • Ensure applications comply with data privacy regulations (e.g., GDPR) and security best practices.
  • Document APIs, architecture decisions, and AI integration workflows for cross-team collaboration.

What we're looking for

  • Bachelor’s/Master’s in Computer Science, Software Engineering, or equivalent experience.
  • 3+ years in full stack development (frontend + backend).
  • Hands-on experience with AI/ML integration (e.g., calling LLM APIs, deploying models, or working with RAG systems).
  • Proficiency in modern frameworks: Frontend: React; Backend: Python (FastAPI, Django, Flask), Node.js, or Java/Spring.
  • Databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis).
  • Cloud: Azure, AWS, or GCP (e.g., serverless, Kubernetes).
  • Familiarity with AI tools/libraries (e.g., LangChain, Hugging Face, TensorFlow Serving) is a plus.
  • Experience with vector databases (e.g., Elastic, chromaDB) or retrieval systems is nice to have.
  • Knowledge of conversational AI (e.g., chatbots, voice assistants) is a plus.
  • Background in financial services, healthcare, or regulated industries is a plus.
  • Strong problem-solving and debugging skills.
  • Ability to collaborate with AI teams, designers, and product managers.
  • Ownership of features from development to production.
  • Clear communication and documentation skills.

Skills

  • React
  • Python
  • FastAPI
  • Django
  • Flask
  • Node.js
  • Java
  • PostgreSQL
  • MySQL
  • MongoDB
  • Redis
  • Azure
  • AWS
  • GCP
  • Kubernetes
  • Prometheus
  • Grafana
  • ELK