should i focus on learning core machine learning/ deep learning or include applied AI engineering skills too for a better chance of being hired

hello everyone i just needed this clarity before wasting my time on learning wrong things, should i focus only on core ML or do i need to include some applied AI skills to my cv, like langchain, vectordb, building a rag pipeline and stuff like that. the reason for me asking this is because i think someone learning ML/DL or any specialisation like MLOps cannot get an entry level jobs in these specific fields, even the entry jobs that are titled as 'ML Engineer', are actually just applied ai engineer, where, say a company only want you to use an already existing model and integrate it with some product/system. so without the AI engineer skills, getting a pure ML engineer job as a fresher would be very hard. can i get some explanation on this please?