Daniel Gruner

After five exciting years as the team leader of the 'Computer Vision Retail' team, during which I took on leadership responsibilities and also contributed my technical expertise as a consultant and solution architect, it is time for a new challenge for me.

Together with internal and external partners, my team colleagues and I design, implement and operate IT solutions in the fields of video security, computer vision, AI, 3D visualization, 3D rendering, 360-degree imaging, virtual reality (VR), augmented reality (AR) and many other exciting topics for the Schwarz Group (Lidl, Kaufland).

As Solution Architects, my team and I are responsible for the design, implementation and operation of IT solutions along the entire solution life cycle for our internal customers of the Schwarz Group. Therefore we elaborate all the requirements from the business but also from the areas of IT security, enterprise architecture, infrastructure etc. We then start to create a concept. For this purpose we also do market research, prototypes and proof of concepts. We evaluate and select the most suitable technologies for the IT solution in terms of performance and economic efficiency. We are responsible for the successful implementation of the IT solution and its integration into our IT landscape. Subsequently we do one or multiple pilots in real world conditions (e.g. in one or more Lidl or Kaufland countries). We manage the GoLive and the roll out. In most cases, we are also responsible for the operations, the 2nd level support and the continuous development of the IT solution. We are the interface between business and IT.

My tasks included not only the development of work packages in the frontend and backend, but also the technical lead, the system design and the stakeholder management (e.g. requirements engineering and workshops with customers, collaboration with infrastructure, data privacy, information security).

The chatbot was designed as a modern web application (frontend: React and several tools and frameworks; backend: Boot, It had various interfaces to existing software systems (e.g. ARIS, Now) as well as to the enterprise IDP via oAuth. We developed and used a hybrid NLU (rule and machine learning based). The ML based part was Microsoft LUIS. We used Service Now as ticketing and Azure DevOps with Git as repo and management tools. We did operate the chatbot on our own on Linux VMs using an Apache Http Server.