AI engineering has gone from a specialism to a line item on most technology roadmaps in about two years, and hiring for it has not caught up. The titles are unstable, the skills people list are not always the skills they have, and the salary expectations move faster than any published survey. These posts cover what an AI engineer, an applied scientist and an MLOps engineer each actually do, how to tell them apart on a resume, and what we are seeing on live searches. Written for hiring managers and technology leaders who need to fill these roles rather than read about the field.