Expert in AI/NLP/ML

We currently have a vacancy for an Expert in AI/NLP/ML fluent in English, to offer his/her services as an expert who will be based in Brussels, Belgium. The work will be carried out either in the company’s premises or on-site at the customer's premises. In the context of the first assignment, the successful candidate will be integrated into the Development team of the company that will closely cooperate with a major client’s IT team on-site.

Tasks:

• Engaging with Business stakeholders, organising workshops and meetings to gather requirements;
• Analysing needs in the archiving domain and translating them into robust technical specifications;
• Designing and proposing AI- and cloud-based architectures that are secure, scalable, and costeffective;
• Developing, testing, and deploying solutions leveraging Large Language Models (LLMs), vector databases, and orchestration frameworks (e.g., LangChain);
• Building prototypes, Proofs of Concept, and production-ready services using Python and Jupyter Notebooks;
• Leveraging AWS Cloud Services (e.g., S3, Lambda, SageMaker, Bedrock, API Gateway, ECS/EKS, CloudFormation/Terraform);
• Preparing and maintaining technical documentation, ensuring knowledge transfer within the team;
• Integrating solutions into existing data and archiving systems;
• Monitoring, optimising, and supporting deployed solutions over time;
• Collaborating closely with Business, IT Infrastructure, and Security teams to ensure long-term sustainability.

Requirements

• Master’s degree in IT or a relevant discipline, combined with a minimum of 13 years of relevant working experience in IT;
• At least 3 years of experience in LLMs: fine-tuning, prompting strategies, evaluation, and deployment;
• At least 2 years of experience in LangChain or equivalent frameworks for LLM orchestration;
• At least 2 years of experience in Vector databases;
• At least 2 years of experience in Python, with practical use of Jupyter Notebooks;
• At least 2 years of experience in AWS services for AI, data, and cloud-native development;
• At least 1 year of experience in Machine Learning Operations, including CI/CD pipelines and monitoring of AI solutions;
• At least 1 year of experience in data engineering and archiving best practices;
• Good knowledge of Docker, Kubernetes and security best practices in AI and cloud-based deployments would be an advantage;
• Knowledge of DevOps/Infrastructure-as-Code tools beyond AWS (Terraform, Ansible) and data governance frameworks and compliance standards (e.g., GDPR) would be an advantage;
• AWS Solutions Architect, AWS Machine Learning, AWS DevOps Engineer, TensorFlow Developer or equivalent AI/ML credentials, Kubernetes Administrator (CKA), TOGAF or equivalent enterprise architecture framework certifications would be an asset;
• Excellent command of the English language.