An LLM has no goals - it's just a machine optimized to minimize training errors, although I suppose you could view this as an innate hard-coded goal of minimizing next word error (relative to training set), in same way we might say a machine-like insect has some "goals".
Of course RLHF provides a longer time span (entire response vs next word) error to minimize, but I doubt training volume is enough for the model to internally model a goal of manipulating the listener as opposed to just favoring surface forms of response.
But simply by approximating human communication which often models goal oriented behavior, an LLM can have implicit goals. Which likely vary widely according to conversation context.
Implicit goals can be very effective. Nowhere in DNA is there any explicit goal to survive. However combinations of genes and markers selected for survivability create creatures with implicit goals to survive as tenacious as any explicit goals might be.