News
Behind the scenes of a Knowledge Engineer – Interview with Dr. Amir Laadhar

Dr. Amir Laadhar is a seasoned Knowledge Engineer with over five years of extensive experience in industry and academia across Europe. He holds a doctoral degree in Computer Science from the prestigious University of Toulouse, France. His professional expertise lies in the application of semantic technologies and the development of innovative data solutions to overcome complex challenges and provide measurable added value to organisations.
We asked Amir a few questions about his role and the tasks of a Knowledge Engineer at PANTOPIX.
Amir, what are your main responsibilities as a Knowledge Engineer?
As a Knowledge Engineer, my responsibilities span various technical and strategic domains, including:
- Knowledge Graph Databases: Designing, implementing, and maintaining scalable and efficient knowledge graph solutions.
- Ontology Engineering: Developing formal representations of domains to enable semantic interoperability and reasoning.
- Data Engineering Pipelines: Creating robust pipelines to transform, integrate, and prepare data for use in semantic systems.
- LLM Models Integration: Exploring and embedding large language models into workflows to enable interaction with data.
- Technology Evaluation: Staying ahead of the curve by researching and integrating cutting-edge tools and frameworks.
- Leadership and Mentoring: Guiding team members and fostering collaboration to ensure project success and skill development.
What skills and knowledge are especially important in your job?
In my role as a Knowledge Engineer, several skills and areas of knowledge are especially important:
- Semantic Web Technologies: Proficiency in RDF, OWL, SPARQL, and related standards is essential for knowledge graph development.
- Communication Skills: The ability to clearly convey complex ideas to diverse stakeholders is critical for success.
- Software Development Skills: Programming expertise (e.g., Python, Java) to build scalable systems and implement solutions.
- Adaptability to Change: A flexible mindset to quickly embrace new technologies, tools, and methodologies.
What role does AI play in your work?
AI serves as an indispensable tool in my day-to-day activities, including:
- Natural Language Processing: Extracting insights and structuring data from unstructured sources.
- Knowledge Engineering: AI helps with tasks like Named Entity Recognition (NER), entity mapping, and semantic extraction, which significantly enhance the process of building and refining knowledge graphs.
By leveraging AI in these areas, I can streamline workflows, improve accuracy, and boost overall productivity.
How do you collaborate with other teams?
Collaboration is a cornerstone of my work, facilitated through:
- Scheduled Synchronization Meetings: Regularly planned sessions to ensure alignment across teams.
- On-Demand Discussions: Quick, focused interactions when specific issues or opportunities arise.
- Documentation and Knowledge Sharing: Maintaining clear records and resources to ensure seamless inter-departmental communication.
What trends do you see in the future of knowledge engineering?
- LLM and Knowledge Graph Integration: Widespread adoption of large language models to enhance querying, reasoning, and interacting with knowledge graphs.
- Increased Adoption of Knowledge Graphs: More organizations will recognize the value of semantic technologies for data integration and decision-making, as highlighted by Gartner’s industry predictions.
- Automation in Ontology Development: Emerging tools will reduce the manual effort required for creating and maintaining ontologies.
How do you measure the success of a knowledge engineering project?
Success is evaluated through both qualitative and quantitative criteria:
- Client Satisfaction: Positive feedback from stakeholders is the ultimate validation of a project’s impact.
- Achievement of Defined Objectives: Assessing whether the project meets or exceeds its outlined requirements.
- Scalability and Usability: Evaluating how well the solution performs under real-world conditions and its ease of use for end-users.
- Knowledge Reuse: Ensuring the system facilitates long-term knowledge sharing and reusability.
How would you explain knowledge engineering to someone with no technical background?
Knowledge engineering is about organizing information in a way that makes it easy to find, understand, and use. Imagine creating a smart library where every book, article, and note is automatically linked to related materials, making it simple to access exactly what you need, when you need it. It helps businesses make better decisions by connecting and structuring their knowledge.
How do you stay flexible and adapt to changes in technology and knowledge?
As a knowledge engineer, I stay flexible by:
- Continuous Learning: I keep up-to-date with new tools and techniques, like improving my German skills for better collaboration with colleagues.
- Collaboration: I value diverse perspectives from cross-functional teams, ensuring that I integrate different viewpoints into solutions.
- Agility in Problem-Solving: Whether filling in for a colleague or adjusting to changing project needs, I reassess priorities to keep projects on track.
- Clear Communication: I maintain open communication with stakeholders to align on goals and adapt to new directions effectively.
By combining these strategies, I ensure that I remain adaptable while maintaining the quality and efficiency of my contributions.
Looking for a new professional challenge?
Then become part of our team!
PANTOPIX stands for intelligent solutions in technical communication. With our many years of expertise, we support companies in optimizing their information processes and ensure maximum added value.
Become part of our team and help us shape the digital future of our customers. We look forward to receiving your application!
Contact us
Maraike Heim
Head of Marketing
- maraike.heim@pantopix.com
