Generative AI Data Scientist | Hybrid Role & Impact

Capgemini Invent; Madrid; Hybrid; EUR 55,000 - 90,000; Full time

Benefits offered by this job

Hybrid work

Continuous learning

Collaborative environment

Job summary

Capgemini Invent in Madrid is seeking a Data Scientist / AI Developer to shape, design, and deploy AI-driven solutions across business domains. You will translate business challenges into scalable, value-driven AI applications, leveraging Generative AI, LLMs, and data sources.

You will collaborate with stakeholders, build production-ready Python components, and ensure robust, well-documented deployments within cloud environments (Azure/GCP). Hybrid working and continuous learning are emphasized.

Qualifications

• Strong background in Data Science, AI Engineering, or related fields.
• Professional proficiency in Spanish and English.
• Experience designing and deploying AI/LLM-based solutions.
• Ability to collaborate with business stakeholders and translate needs into technical solutions.

Responsibilities

• Translate business needs into scalable AI applications.
• Design and deploy AI solutions using Generative AI and LLMs.
• Build AI applications leveraging LLMs, RAG, and data sources.
• Develop robust components in Python and integrate with enterprise systems.
• Document, test, and deploy solutions; communicate decisions clearly.

Skills

AI Engineering

Python Development

Generative AI

RAG & Information Retrieval

APIs

Git & DevOps

Cloud Technologies (Azure, GCP)

Business Understanding

Stakeholder Management

Spanish & English

Tools

Git

Azure

GCP

APIs

Job description

Capgemini Invent in Madrid is seeking a Data Scientist / AI Developer to shape, design, and deploy AI-driven solutions across business domains. You will translate business challenges into scalable, value-driven AI applications, leveraging Generative AI, LLMs, and data sources.

You will collaborate with stakeholders, build production-ready Python components, and ensure robust, well-documented deployments within cloud environments (Azure/GCP). Hybrid working and continuous learning are emphasized.