Job main responsibilities:

- Support development and deployment of AI and advanced analytics use cases

- Prepare, validate, and curate data for AI workloads

- Ensure quality, performance, and governance of AI outputs

- Collaborate with data engineering and analytics teams

- Support responsible and scalable AI adoption

Technical Skills & Technology Landscape:

- Machine learning and advanced analytics concepts

- Analytics-ready and AI-ready datasets

- Model validation, monitoring, and performance tracking

- Cloud-based analytics and AI platforms

Qualifications and Skills:

1. Core Technical

- LLM orchestration frameworks: LangChain, Semantic Kernel, Azure AI Foundry

- MLOps practices: model versioning, deployment pipelines, monitoring (MLflow, Azure ML)

- Prompt engineering: few-shot, chain-of-thought, structured output, retrieval-augmented generation (RAG)

- Azure AI Services: Azure OpenAI, Cognitive Services, AI Search (vector and hybrid)

- Feature engineering and ML pipeline development (Databricks Feature Store, MLflow)

- Responsible AI: bias detection, explainability, AI governance frameworks

- AI-ready data design: embedding generation, vector store management, data curation for AI

- API integration: exposing AI capabilities as enterprise services (FastAPI, Azure API Management)

2. Certifications

- Microsoft Certified: Azure AI Engineer Associate — Preferred

- Microsoft Certified: Azure AI Fundamentals — Preferred

- Databricks Certified Machine Learning Professional — Preferred

- Generative AI for Business Leaders (Microsoft / Coursera / DeepLearning.AI) - Strongly Preferred

- Microsoft Certified:



Fabric Analytics Engineer Associate — Preferred

3. Industry & Business Knowledge

- Industrial AI use cases: predictive maintenance, quality control, demand sensing

- SAP data context for AI inputs: finance forecasting, procurement analytics, production data

- Responsible AI governance in a integral manufacturing enterprise

- Understanding of data privacy, AI regulation (EU AI Act), and compliance requirements

- Business value framing: translating AI capabilities into operational impact

4. Behavioral & Leadership

- Innovation mindset balanced with pragmatic delivery

- Ability to translate AI concepts for non-technical business audiences

- Responsible AI advocacy — champions governance alongside capability

- Hypothesis-driven experimentation: tests before scaling

- Strong cross-domain collaboration with data engineering, analytics, and business units

What do we offer?

- Hybrid Work Model: Flexibility to work from home and in the office, according to the policy, helping you achieve a healthy work-life balance.

- Ticket Restaurant: Enjoy a daily meal allowance to support your well-being.

- Flexible retribution: Kindergarten & Transport

- 30 Labor Days of Holidays: Ample time off to relax and recharge.

- Language Lessons: Access to language lessons to help you grow both personally and professionally.

- Medical Insurance: 60% company-subsidized medical insurance for employees, with the option to extend coverage to family members at a highly competitive rate.

- Open and Modern Office Environment: Work in a collaborative, innovative, and comfortable space designed for your success.

📌 AI Lead (España)
🏢 Omya Business Services SLU
📍 España