Additionally, an important mission is to prepare for the future (process automation, development of solution & technologies to bring significant efficiency) in the frame of Customer Services Ambition 2030 ( Efficient TechData cornerstone ). To augment and accelerate this mission, we are looking for a skilled and motivated Artificial Intelligence Engineer to join our team. This role offers a unique opportunity to work at the intersection of knowledge representation and machine learning. You will be responsible for developing our advanced, logically-driven databases while also contributing to the creation of end-to-end AI and Generative AI project pipelines. The ideal candidate is a hands-on developer with a passion for building intelligent systems that combine structured knowledge with modern predictive models.
Key Responsibilities Knowledge Systems & Database Development:
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Design and implement advanced logical databases using frameworks like TypeDB, Neo4j, or Datalog .
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Develop and maintain robust knowledge graph systems to host complex, interconnected data.
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Build intuitive GUI frontends for our databases to enable effective data interaction and exploration.
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Collaborate with data analysts to translate data requirements into effective data models.
Machine Learning & AI Pipeline Development:
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Contribute to the architecture and development of end-to-end ML and GenAI pipelines , from data ingestion to model deployment.
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Build, train, and deploy machine learning models, including work with Large Language Models (LLMs) and techniques like Retrieval-Augmented Generation (RAG).
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Integrate ML models with our core knowledge bases to create powerful, hybrid AI systems.
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Participate in the entire lifecycle of AI projects, ensuring they are scalable and aligned with business goals.
Required Qualifications & Competencies - Bachelor s and / or Master s Degree in Computer Science Engineering, with 4-8 years of professional experience in a software engineering or data-focused role.
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Solid Experience in Database Development: Demonstrable experience building and managing databases, with a strong preference for knowledge graphs (TypeDB, Neo4j) or logical databases (Datalog).
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Proficiency in Knowledge Representation: A good understanding of knowledge representation principles.
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Experience with ML Pipelines: Hands-on experience developing components of machine learning pipelines using Python and relevant frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
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Familiarity with Generative AI: Understanding of GenAI concepts, including LLMs and vector databases.
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Full-Stack Capability: Ability to contribute to development across the stack, from the database backend to the GUI frontend.
Preferred Qualifications -
Exposure to digital transformation in the aerospace / automotive industry will be an added advantage.
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Familiarity with expert systems or Hierarchical Task Networks (HTN) .
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Experience with MLOps tools (e.g., MLflow, Kubeflow) or cloud AI platforms
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A portfolio of projects that showcases your skills in database development and machine learning.
. Professional and technical skills
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Excellent communication/presentation skills, both oral and written, with advanced knowledge in profession / technical English language.
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Good coordination and relational skills to deal with internal and external stakeholders
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Ability to learn and adapt with evolving technologies.
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LEAN tools and methodologies - Value Stream Mapping, Problem solving and Improvements
b. Behavioral skills
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Proactive mindset with a focus on customer satisfaction
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Analytical thinking and problem solving skills
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Assertiveness in communication style
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Good team player with organizational skills - ability to work with local and transnational team members
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Customer mindset
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Collaborative attitude
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Organized, engaged, adaptable and flexible
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Curious, enthusiastic & open-minded
