Cognitive systems are starting to be deployed as appliances across the technological landscape of modern societies. The increasing availability of high performance computing platforms has opened an opportunity for statistics-based cognitive systems that perform quite as humans in certain tasks that resisted the symbolic methods of classic artificial intelligence. Cognitive artefacts appear every day in the media, raising a wave of mild fear concerning artificial intelligence and its impact on society. These systems, performance notwithstanding, are quite brittle and their reduced dependability limips their potential for massive deployment in mission-critical applications -e.g. in autonomous driving or medical diagnosis. In this paper we explore the actual possibility of building cognitive systems using engineering-grade methods that can assure the satisfaction of strict requirements for their operation. The final conclusion will be that, besides the potential improvement provided by a rigorous engineering process, we are still in need of a solid theory -possibly the main outcome of cognitive science- that could sustain such endeavour. In this sense, we propose the use of formal ontologies as backbones of cognitive systems engineering processes and workflows.