Descripción de la oferta
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
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)
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
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 global manufacturing enterprise
Understanding of data privacy, AI regulation (EU AI Act), and compliance requirements
Business value framing: translating AI capabilities into operational impact
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.
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