AI & Automation Intern
- • Identify a practical business automation use case.
- • Build a small approved proof of concept.
- • Evaluate output quality and failure scenarios.
- • Document limitations, privacy and security considerations.
Advanced learning pathway
Data and responsible AI
- • Python and data preparation
- • Privacy, consent and bias
- • Evaluation datasets and baselines
A documented dataset and reproducible baseline evaluation.
Intelligent workflows
- • APIs, webhooks and retries
- • Retrieval-augmented generation
- • Tool use, structured output and human review
A supervised automation with explicit approval boundaries.
Reliability and evaluation
- • Prompt injection and data leakage
- • Cost, latency and monitoring
- • Regression evaluation and failure recovery
An evaluated automation capstone with safety and recovery documentation.
Deliverable
A demonstrable prototype or documented proof of concept, test report and technical handover.
Preferred skills
Logical thinking, basic programming or workflow automation.
No unauthorized production access, confidential datasets or paid services without approval.
100 vacanciesDetails