AI Engineer (JHB Hybrid)

ENVIRONMENT:

JOIN an applied-AI work on a structured, mentored pathway, rotating through the data engineering that feeds it as the next AI Engineer wanted by a provider of tailored Financial Solutions. You will prepare trusted data for AI workloads, help run an in-house governed AI platform, and test AI-assisted use cases under supervision and strictly inside policy. This is an engineering-and-governance internship, not a research post, and you will not be training bespoke models. What you will learn is how AI gets used safely and usefully on real, sensitive data in a regulated business. Interns who grow well here are first in line as the team expands, and the combined Data & AI Engineer role is the named destination on the team's growth path. Candidates will require foundational Python, whether from coursework, projects, or self-teaching, but you must be able to read, run, and modify a script & a basic understanding of SQL and relational data concepts.

DUTIES:

· Prepare, clean, validate, and document the datasets that AI and search workloads consume.

· Support the in-house governed AI platform: content ingestion, indexing, configuration, and routine health checks under supervision.

· Test and evaluate AI-assisted use cases such as summarisation, classification, search, extraction, and automation against defined success criteria.

· Write small Python scripts and notebooks to automate repetitive data preparation and evaluation tasks.

· Record evaluation evidence: what was tested, what the AI produced, what a human reviewer changed, and why.

· Apply data-minimisation and anonymisation rules without exception, which means no personal information, credentials, or production data goes into unapproved tools.

· Contribute to documentation: use-case write-ups, prompt and configuration notes, data dictionaries, and testing evidence.

· Learn the company governance, security, privacy, and change management standards from day one.

· Attend team ceremonies and give clear, honest progress updates on assigned tasks.

What you’ll work with –

· A governed in-house AI platform, where you will learn to use AI tools properly, with controls, from week one.

· Python, notebooks, and Git, giving you modern engineering habits from the start.

· SQL Server and Microsoft Fabric, the governed data estate that feeds every AI use case.

· Power BI, which is how results reach the business.

· Evaluation and human-review workflows, which are how we decide whether an AI output is good enough to use.

REQUIREMENTS:

· Foundational Python, whether from coursework, projects, or self-teaching, but you must be able to read, run, and modify a script.

· Basic understanding of SQL and relational data concepts.

· Practical curiosity about AI tools, paired with healthy scepticism about their output.

· Attention to detail and willingness to document work clearly.

· Good written and verbal communication, and genuine appetite to learn.

· Awareness that data is sensitive and that confidentiality is non-negotiable.

Advantageous -

· Qualification in progress or recently completed in Data Science, Computer Science, Information Systems, Statistics, Mathematics, Engineering, or related.

· Exposure to APIs, notebooks, retrieval / vector search concepts, or any LLM tooling.

· Any project where you used AI to solve a real problem, especially if you can explain where it got things wrong.

· Portfolio, coursework, hackathon, or capstone evidence of data or AI problem-solving. Show us anything you have built.

· Basic awareness of responsible-AI concerns: bias, hallucination, privacy, and traceability.

ATTRIBUTES:

· You verify before you trust, and that includes AI output above all.

· You learn fast and enjoy it, because new tools and feedback energise you rather than intimidate you.

· You can explain what a tool actually did, not just that it seemed to work.

· You check your work and ask when unsure, with no silent guessing.

· You want a career in data or AI, not just a gap-filler job.

· Integrity and values, with the ability to handle sensitive and confidential information.

· Attention to detail and a results-driven quality mindset.

· Strong problem-solving; composure in a fast-moving, dynamic environment.

· Works well in a team and independently; communicates openly.

· Growth mindset, actively wanting to learn and develop.