Full-Stack AI Engineer for Insight Platform

Mondelēz International; Barcelona; On-site; EUR 60,000 - 90,000; Full time

Job summary

Mondelēz International in Barcelona is seeking a Full Stack AI Engineer to help build a new AI-powered insights platform. You’ll design data pipelines, develop AI/ML components, and ship full stack applications that surface insights for global and regional users.

You will collaborate with Product, Data Science, and Business stakeholders to translate requirements into technical designs, write clean, tested code, contribute to platform architecture, and uphold best practices in CI/CD, security,

Qualifications

• Experience designing and delivering production-grade apps or data pipelines.
• Ability to work with cross-functional teams and external vendors.
• Strong understanding of cloud platforms and data architectures.
• Familiarity with AI/ML workflows and LLM-based tasks.
• Good communication and documentation skills.

Responsibilities

• Design, build, and maintain data pipelines ingesting and transforming market data.
• Develop and deploy AI/ML models and RAG workflows.
• Build full stack apps (APIs, services, front-end) surfacing AI insights.
• Implement monitoring, logging, and cost optimization in production.
• Collaborate with Product, Data Science, and Business stakeholders to translate requirements into designs.
• Contribute to platform architecture decisions (Terraform, Docker, CI/CD).
• Write clean, tested code and participate in code reviews and sprints.

Skills

Vendor management

Project management

Stakeholder management

Infrastructure delivery

Python

AI/ML

Data engineering

Tools

Python

AWS

Databricks

Terraform

Docker

React

Next.js

LangChain

Job description

Mondelēz International in Barcelona is seeking a Full Stack AI Engineer to help build a new AI-powered insights platform. You’ll design data pipelines, develop AI/ML components, and ship full stack applications that surface insights for global and regional users.

You will collaborate with Product, Data Science, and Business stakeholders to translate requirements into technical designs, write clean, tested code, contribute to platform architecture, and uphold best practices in CI/CD, security,