Internship - AI Incident Reporting Assistant

PFE (stage de fin d'études) chez Axe Finance, Tunis — sur site, temps plein. Joining Axe Finance is joining a fast-growing fintech company. We are currently seeking to hire (a) PFE intern(s) Key Responsibilities: Study the current incident lifecycle (bank user → support → ticketing tool) and design the target automated flow. Develop an in-app "Report an incident" feature in ACP that automatically captures context: screenshot and user action trail (steps performed), error logs and stack trace, module, version, environment and related application ID. Build an LLM-based engine that turns the user's description and the captured context into a structured ticket: title and steps to reproduce, expected vs. actual behavior, suggested severity, priority and module classification. Detect duplicate incidents through semantic similarity against existing tickets (embeddings and a vector database), and suggest known workarounds. Integrate with the ticketing tool via REST API (Jira, ServiceNow or similar) to create tickets automatically and return their status to the user. Ensure banking-grade compliance: masking of personal data, confidentiality and an audit trail. Measure impact (ticket completeness, triage time), then document and demo the solution. Candidate Profile Requirements Final-year engineering or master's student in Software Engineering, AI or Data Science. Good skills in Java and a web front-end framework (Angular or React), plus Python. Knowledge of NLP and LLMs, including RAG, embeddings and prompt engineering. Experience integrating REST APIs; familiarity with Jira or other ticketing tools is a plus. Awareness of data privacy and security concerns. Analytical mindset, rigorous, and comfortable in French and English.

Joining Axe Finance is joining a fast-growing fintech company. We are currently seeking to hire (a) PFE intern(s) Key Responsibilities: Study the current incident lifecycle (bank user → support → ticketing tool) and design the target automated flow. Develop an in-app "Report an incident" feature in ACP that automatically captures context: screenshot and user action trail (steps performed), error logs and stack trace, module, version, environment and related application ID. Build an LLM-based engine that turns the user's description and the captured context into a structured ticket: title and steps to reproduce, expected vs. actual behavior, suggested severity, priority and module classification. Detect duplicate incidents through semantic similarity against existing tickets (embeddings and a vector database), and suggest known workarounds. Integrate with the ticketing tool via REST API (Jira, ServiceNow or similar) to create tickets automatically and return their status to the user. Ensure banking-grade compliance: masking of personal data, confidentiality and an audit trail. Measure impact (ticket completeness, triage time), then document and demo the solution. Candidate Profile Requirements Final-year engineering or master's student in Software Engineering, AI or Data Science. Good skills in Java and a web front-end framework (Angular or React), plus Python. Knowledge of NLP and LLMs, including RAG, embeddings and prompt engineering. Experience integrating REST APIs; familiarity with Jira or other ticketing tools is a plus. Awareness of data privacy and security concerns. Analytical mindset, rigorous, and comfortable in French and English.