Most AI projects end in a slide deck. Ours go live.

Lugano, Switzerland or remote within the EU

About PHILIPP PLEIN

PHILIPP PLEIN is a Swiss luxury fashion group with several brands, stores and online shops around the world. We are AI-first: we rethink how the work is done, then build it with AI. What you build lands directly with our merchandise, allocation, finance and operations teams.

What you will do

• Learn how our tech stack works end to end and find the weak spots: slow, costly, fragile or outdated.

• Fix those spots (speed, cost, stability, security, clean code), then keep them healthy.

• Build AI-driven solutions end to end, frontend, backend and database, from first idea to daily use.

• Build agents and web apps for business teams; connect product, PLM and sales data (read only).

• Run ETL pipelines with Airflow: gather data from all systems, clean it, check it, improve it.

• Track every app, agent and pipeline: who did what, errors, cost and quality, so you can fix fast and keep improving.

What you bring

• Experience: 3 to 5 years as a developer shipping software to production, at least one LLM solution used by real people, fluent English.

• Frontend: TypeScript, React or Next.js; clear, fast screens for business users.

• Backend: Python (FastAPI) or Node.js; REST APIs, sign-in, background jobs, automated tests.

• Databases and data: PostgreSQL, strong SQL, data modelling, migrations, query tuning; ETL orchestration with Airflow, data quality checks, dbt, Snowflake or Databricks.

• LLMs and agents: Claude and OpenAI APIs, prompts with cost limits, structured output, MCP, multi-agent with human approval (LangGraph, Pydantic AI or Claude Agent SDK), RAG, embeddings, vector search (pgvector), tool calling.

• Data science: pandas, scikit-learn, PyTorch, LightGBM or statsmodels; forecasts tested on past seasons.

• Governance and tracing: access rights, GDPR and Swiss data law, versioned prompts and models; audit trail (who, when, old to new); run tracing (Langfuse or similar), error tracking (Sentry or similar), cost, speed and quality per call, test sets for LLM answers.

• AI coding and delivery: Claude Code, Cursor or Copilot every day; you review, test and fix what the tool writes. Docker, Azure or another cloud, CI/CD with GitHub Actions.

• Working skills: process mapping; turning what users say into clear specs and tickets.

Who you are

• You start from the work, not the model.

• You ship things people use, then make them better.

• You check every number and every AI answer before you trust it.

• You explain your work in simple words, so anyone in the company can follow.

How to apply

Apply here on LinkedIn with your CV and answer one question.

👉 Show us one thing you built with AI coding tools. What did the AI get wrong, and how did you fix it?

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