Jelle Scholtalbers

Backend-focused full-stack and AI engineer (Django/DRF + Vue.js) with a scientific computing background, specializing in data-intensive, research-driven, and AI-enabled applications.

Engagements run end-to-end, from user requirements through architecture, implementation, and production deployment. Scope covers UI design, data modeling, API contract design, and asynchronous processing.

Backend. Scalable Django + PostgreSQL systems with REST APIs, caching layers (Redis/Memcached), and message brokers (RabbitMQ). Robust authentication (JWT, OAuth) and production concerns such as automated backups and scheduled jobs are part of the standard delivery.

AI engineering. Integration of LLM-powered capabilities into existing products and workflows. This includes building AI chat assistants grounded in business context, selecting and switching between different model providers and deploying AI features in production environments. Comfortable rapidly exploring new domains and translating subject-matter expertise into effective AI-assisted user experiences.

Deployment & infrastructure. Applications are containerized with Docker and deployed on Kubernetes, backed by reliable GitLab CI/CD pipelines and cloud-native infrastructure.

Strict code-quality discipline: type hints, testing, pre-commit hooks, and technical documentation (MkDocs). Agentic coding workflows amplify all of this: spec-to-shipped-feature cycles compress, while automated review, testing, and structured planning hold the quality bar high.

Adjacent experience. HPC-based scientific workflows, GitLab administration for a large research institute. A core developer of the LabID open-source project, and a multi-tenant SaaS with schema-level data isolation (django-tenants) built on top of it.

Most useful when you need a senior generalist who can own a feature end-to-end, integrate modern AI capabilities into existing products, and who can also speak the language of the scientists you're building for.