AI-related job titles vary between employers. Read the actual responsibilities and build evidence of the work you can perform. The descriptions below are examples of task areas, not current vacancies or salary forecasts.
Prompt engineer and AI consultant
Prompt work involves clear instructions, representative test cases and checking outputs against a defined task. AI consulting also requires interviews, process analysis and deciding whether AI is useful at all. Portfolio example: an approved brief, a set of test inputs and a documented improvement; for consulting, add a reasoned scope and a measurable pilot.
AI product manager and automation engineer
Product work connects a user problem to acceptance criteria, delivery choices and observed outcomes. Automation engineering also requires reliable integrations, access controls, failure recovery and monitoring. A no-code prototype demonstrates part of this work; production engineering requires additional technical skills.
AI marketing specialist and creative director
Marketing work joins audience research, credible offers, content planning and review of real response data. Creative direction involves the brief, visual consistency, reference selection and approval of final assets. AI-generated examples should be labelled where needed and must not misrepresent a real product or client result.
Build evidence before making career claims
Create a small portfolio showing the brief, source material, your decisions, the finished output and its limitations. Obtain permission before sharing client work. Compare current job requirements with gaps in your skills. Include research, editing and communication time when evaluating paid work; learning a tool does not guarantee a salary or a business result.
Keep this checklist
- Role responsibilities checked
- Portfolio shows your decisions
- Technical gaps identified
- Client material shared only with permission
This is an original practical guide. Examples are illustrative; tool interfaces and available features may change.