AI Engineer

Responsibilities

• The AI Engineer designs, deploys and industrializes generative AI, machine learning and automation solutions to support various business functions (education/pedagogy, learner relations, internal teams)
• Transform concrete business needs into reliable, measurable and controlled AI products (costs, latency, compliance), from scoping through production
• Define and scope requirements expressed by different teams, estimate ROI and make build-vs-buy and implementation trade-offs
• Design and industrialize generative AI and ML solutions: RAG (retrieval-augmented generation), educational and administrative chatbots, agents, automations
• Document, harden and evolve solutions (CI/CD, Dev/Staging/Prod environments)

Qualifications

• Minimum level-5 qualification required (e.g., two-year higher education diploma/associate degree)
• Read/write Python, strong fundamentals in programming and best practices (pytest testing, typing/validation with Pydantic) — required
• Agentic coding tools (Claude Code, Codex, etc.), adopting a “Vibe Engineering” rather than “Vibe Coding” approach — required
• Git (Git

  Hub/Git

  Lab), rigorous repository management, documentation and CI/CD — required
• Docker and Dev/Staging/Prod environments — required
• Knowledge of GDPR and the AI Act — required
• Personal data handling / anonymization (PII), with particular attention to audio transcriptions — required