Key points
- Most businesses need implementation and automation roles before engineering roles.
- Titles vary between companies; read the responsibilities, not the title.
- Use this glossary to write clearer job briefs.
AI job titles are inconsistent across the market. This glossary explains what each role usually does.
| Role | What they do | Who needs one |
|---|---|---|
| AI implementation lead | Turns AI tools into working business processes and measured savings | Any company adopting AI at scale |
| Automation specialist | Builds workflows on automation and AI platforms, connects systems | Companies automating several processes |
| AI solutions architect | Designs how enterprise AI tools connect to systems, data and security | Larger companies with complex systems |
| AI trainer / enablement lead | Trains staff and drives everyday AI adoption | Companies with many non-technical users |
| AI product manager | Turns business problems into AI features and internal tools | Companies building their own AI products |
| Head of AI / Chief AI Officer | Owns AI strategy, budget, governance and team | Organisations with AI across several units |
| Generative AI / LLM engineer | Builds custom assistants and agents on leading models | Companies building tailored AI applications |
| Data engineer | Builds the pipelines and platforms AI depends on | Companies with significant data systems |
| Data scientist | Analyses data and builds predictive models | Companies with modelling needs |
| Machine learning engineer | Builds, trains and deploys ML models | Companies developing their own models |
| MLOps engineer | Runs models reliably in production | Companies with models in production |
| AI governance / risk specialist | Manages responsible AI, model risk and compliance | Regulated sectors |
Which roles to hire first
For most companies the first hires are an AI implementation lead and, as volume grows, one or two automation specialists. Engineering and data science roles come later, if at all, when you start building your own products or models.
Writing the brief
Describe the outcomes you expect in the first year, the processes involved, the systems the person will work with and who they will report to. A clear brief attracts better candidates than a long list of technologies.
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