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# AI Specialist (Junior to Medior) - Generative AI / LLM - Brussels

- **Company:** Allo Interim
- **Location:** Brussel, Belgium (Remote available)
- **Experience:** Starter
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Continuous Integration, Extract Transform Load (ETL), Python (Programming Language), Open Source Technology, Power BI, Search Technologies, SQL Databases, Private Cloud Environment, Chatbots, Flask (Web Framework), Large Language Models, Prompt Engineering, Spring-boot, Generative AI, Fastapi, AI Platforms, Kubernetes, Information Technology, Machine Learning Operations, Data Pipelines, Docker, Microservices
- **Published:** September 18, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=684bedbcc8a2427b

## About the Role

* Bachelor's or Master's degree in Computer Science, IT, AI, Data Science or related field
 * Proficiency in Python and Java
 * Demonstrated mastery of prompt design, evaluation, optimisation and model behaviour analysis
 * Hands-on experience with LLMs, text embeddings, vector databases, open-source models and AI APIs
 * Solid understanding of AI solution architecture, Docker/Kubernetes, private cloud, CI/CD and MLOps
 * Strong analytical and problem-solving skills
 * Excellent English (verbal and written); French is a distinct advantage

NICE-TO-HAVE

 * FastAPI, Spring Boot or Flask
 * Vector search engines such as Qdrant
 * Document processing / OCR tools
 * SQL, ETL/ELT pipelines, data modelling, orchestration, Power BI
 * Business case analyses or AI maturity assessments

## Description

* End-to-end AI development: design, develop, test and deploy AI solutions, PoCs, pilots and production-ready applications
 * Enterprise AI platforms: contribute to the evolution, deployment and scaling of AI platforms, intelligent chatbots and AI microservices
 * Document & knowledge automation: optimise business processes, legal document categorisation and semantic knowledge retrieval
 * Generative AI engineering: build solutions using LLMs, embeddings, vector databases and modern AI APIs
 * Technical collaboration: translate functional requirements into scalable, high-performance AI architectures
 * Architecture & documentation: author technical specifications, architecture deliverables and reusable components
 * MLOps: participate in deployment, industrialisation, monitoring and support of production AI systems
 * Best practices: drive standards, internal training and continuous improvement
 * Agile teamwork within multidisciplinary teams


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