Originally published on AI Tech Connect.
What you need to know If you already build models — you have trained gradient-boosted trees, tuned a neural net, argued about leakage in a cross-validation split and defended a metric to a sceptical stakeholder — then the move into LLM engineering is not the career reset the job adverts make it feel like. It is a translation. You are not starting from zero; you are re-pointing skills you already have at a different kind of system. The awkward part is that the material which is genuinely new was never on your data-science syllabus, while the skills you are strongest at are quietly the most valuable thing an LLM team can hire. This guide is the 90-day plan to make that translation legible to the people doing the hiring, in both India and the United Kingdom. This is deliberately not the…
Top comments (0)