? Designed and developed a highly scalable and modular web service using Azure and Terraform, enabling seamless expansion and enterprise-level deployment.
? Architected the infrastructure and system architecture, ensuring a secure, reliable, and efficient structure suitable for selling as a multi-tenant enterprise solution.
? Built a full-stack booking system, including frontend, UI (Next.js/React) , backend, API integrations, database management, and secure server deployment.
? Implemented automated infrastructure provisioning with Terraform, optimizing deployment, scalability, and maintainability.
? Ensured high security standards, including authentication, encryption, and compliance with best practices for cloud-based applications.
? Creation of a ChatBot for Recruiters to retrieve Information about Candidates, Jobs etc. in a custom defined way to improve productivity of Recruiters. Developing the UI with Streamlit.
? Migration of Clients system from Azure to AWS
? Creation of various AI-tools to help Recruiters decide which Canidate is the best fit. Atomisation of the Recruiting Job.
? Planning and Managing of QDRANT and PostgreSQL for the AI-Tools
? Building complete Infrastructure (Backend, Cloud, API, etc.) for the Clients Product.Creationof an Enrichment AI-Agent workflow to Enrich missing data of given product ERMs.
? Implementing Web-scraping/Searching, Parallelisation etc.
? Creation of CI/CD Pipelines
- Planung und Implementierung eines Systems zur bidirektionalen
Zuordnung zwischen Chat-Dialogen und dem Wissensgraphen als RAG.
- Dieses Projekt ermöglicht die Extraktion und Integration von
? Developed a tool to analyze repositories and assign business value, aiding in risk prioritization
and management.
? The Tool consist of different AI tools combined in a Graph.
? Finetuning of LLM Models
? Usage of OpenSource Models and Agents
? Planned and Implemented a system that aims to implement a bidirectional mapping between chat dialogues and the knowledge graph as RAG.
? This Project has the ability to extract and integrate conversational data into a dynamic graph structure in both directions, providing an efficient user experience in managing cybersecurity data and dialogues.
die Konfigurationszeit pro Instanz um bis zu 30 Stunden reduziert wurde.
Erzielung einer Genauigkeit von 96% bei der Link-Vorhersage für
domänenspezifische Wissensgraphen.
- Zusammenarbeit mit funktionsübergreifenden Teams zur Datenerfassung
und zum Verständnis der Domäne
? Designed and developed a highly scalable and modular web service using Azure and Terraform, enabling seamless expansion and enterprise-level deployment.
? Architected the infrastructure and system architecture, ensuring a secure, reliable, and efficient structure suitable for selling as a multi-tenant enterprise solution.
? Built a full-stack booking system, including frontend, UI (Next.js/React) , backend, API integrations, database management, and secure server deployment.
? Implemented automated infrastructure provisioning with Terraform, optimizing deployment, scalability, and maintainability.
? Ensured high security standards, including authentication, encryption, and compliance with best practices for cloud-based applications.
? Creation of a ChatBot for Recruiters to retrieve Information about Candidates, Jobs etc. in a custom defined way to improve productivity of Recruiters. Developing the UI with Streamlit.
? Migration of Clients system from Azure to AWS
? Creation of various AI-tools to help Recruiters decide which Canidate is the best fit. Atomisation of the Recruiting Job.
? Planning and Managing of QDRANT and PostgreSQL for the AI-Tools
? Building complete Infrastructure (Backend, Cloud, API, etc.) for the Clients Product.Creationof an Enrichment AI-Agent workflow to Enrich missing data of given product ERMs.
? Implementing Web-scraping/Searching, Parallelisation etc.
? Creation of CI/CD Pipelines
- Planung und Implementierung eines Systems zur bidirektionalen
Zuordnung zwischen Chat-Dialogen und dem Wissensgraphen als RAG.
- Dieses Projekt ermöglicht die Extraktion und Integration von
? Developed a tool to analyze repositories and assign business value, aiding in risk prioritization
and management.
? The Tool consist of different AI tools combined in a Graph.
? Finetuning of LLM Models
? Usage of OpenSource Models and Agents
? Planned and Implemented a system that aims to implement a bidirectional mapping between chat dialogues and the knowledge graph as RAG.
? This Project has the ability to extract and integrate conversational data into a dynamic graph structure in both directions, providing an efficient user experience in managing cybersecurity data and dialogues.
die Konfigurationszeit pro Instanz um bis zu 30 Stunden reduziert wurde.
Erzielung einer Genauigkeit von 96% bei der Link-Vorhersage für
domänenspezifische Wissensgraphen.
- Zusammenarbeit mit funktionsübergreifenden Teams zur Datenerfassung
und zum Verständnis der Domäne