Overview
Obtenga más información sobre las tareas generales relacionadas con esta ocasión a continuación, así como sobre las habilidades requeridas.
In this AI Engineer role, you design and operate scalable analytics pipelines and enterprise-grade agentic workflows to deliver data-driven AI solutions. You join the Data & AI Organization (MDAO) to partner with Product Owners, Data Engineers, and Data Scientists across functions, translating insights into actionable outcomes. You embed explainability, security, and observability into AI solutions and leverage modern platforms to scale impact. This role offers hands-on work with LLMs, predictive models, and multi-agent systems to address business challenges and strategic data products. You will contribute to AI literacy and drive innovation across the organization.
Responsabilidades
Design and implement analytics pipelines and agentic workflows
Integrate LLMs, predictive models, and multi-agent frameworks
Ensure model reliability, reproducibility, and enterprise-scale performance
Collaborate with PODs and cross-functional teams to deliver AI outputs via APIs, dashboards, and embedded analytics




Support business teams in consuming AI outputs and building user-facing insights
Contribute to internal AI literacy through mentoring and knowledge sharing
Experiment with new AI approaches and measure impact
Maintain awareness of security, explainability, and governance in AI solutions
Requisitos principales
5+ years of experience in data science, data engineering, analytics, or visualization
Experience with Finance, HR, or Procurement data and core business processes
Excellent programming skills in Python and SQL
Strong foundation in ML, statistics, predictive modeling, and xqbhyrx NLP with LLMs
Familiarity with vector stores, reranking, and LLM observability tools (Langfuse, LangSmith)
Experience with agentic engineering tools (Claude Code, OpenAI Codex, OpenCode)
Experience with cloud/enterprise data platforms (AWS, Palantir Foundry, Snowflake) and data frameworks (Spark, polars, DuckDB, dbt)
MLOps & DevOps experience (MLflow, CI/CD, Docker)
Curiosity about AI trends and strong communication in English; German a plus
excellent communication
collaboration
curiosity
Python
SQL
ML/AI

📌 (Senior) AI Engineer - Data & AI Organisation (all genders)
🏢 Merck
📍 Barcelona