I think using the vision decoder baked into modern LLMs is the way to go. Have the LLM iterate; make sure it can assert placement qualities and understands the hard requirements. I think it can be done.
Take for example something like XinZhiZao (XZZ), ZXW, Wuxinji, diyfixtool. They have huge databases with pictures, diagrams and boardviews of pretty much every phone, laptop and graphics card. With all this data you could build AI system ripping of^^^^^ "suggesting" routing for your design based on similarity to stole^^^training data. That way you start with layout that worked in devices shipped by the millions.
This could be build in stages, starting witch much weaker system trained on just pcb pictures + layer count. This should be enough to suggest ~optimal initial chip placement for classical auto-router.