I describe my profession as cognitive science or cognitive systems architect - my early work was in computational linguistics and knowledge representation (artificial intelligence), my mid career has been in understanding better the limitations of humans and trying to compensate with technology. This has led me to explicit cognitive models (in the Simon and Newell sense), though I should also thank my graduate advisor James Allen for pointing me in the direction of using plans to represent an agent's intentions (both at a domain and discourse level), as well as the centrality of Problem Solving (which ultimately stems from Simon's work on GPS). Note that I distinguish between the goal of cognitive science - understanding natural intelligence and using systems to test theories - as distinct from artificial intelligence - building systems that 'act intelligent'. Some of the methods are similar, but a cognitive scientist isn't going to be happy with a model unless it matches some modeled population, while AI generally doesn't care so long as it 'did the right thing.'
I'm very interested in the relationship between different kinds of (human) memory: episodic, semantic and procedural; child knowledge acquisition; distributed problem solving (particularly under time constraints) and "intuition, imagination and insight" to quote Simon.