I am an industrial engineer with broad international experience and a strong focus on digital transformation and generative AI. I enjoy building practical technology solutions that improve operations, customer experience, and decision-making.
My background combines industrial engineering, mechatronics, data science, and AI. I have worked on Industry 4.0 initiatives, predictive maintenance, and AI-driven automation, using tools such as Python, IoT, machine learning, and cloud platforms.
I have led and contributed to Generative AI and LLM projects, including proof-of-concepts, MVPs, and production-ready multi-agent systems. My work has involved LangChain, LangGraph, Azure AI Services, OpenAI API, RAG architectures, and MLOps practices.
I am comfortable working across the full AI delivery lifecycle, from problem analysis and solution design to deployment and operational support. I have experience with CI/CD pipelines, Docker, Kubernetes, Azure DevOps, and scalable cloud-based architectures.
I value teamwork, innovation, and cross-functional collaboration. I have worked in international environments across Spain, Belgium, and Switzerland, and I bring a consulting mindset to technical challenges.
My goal is to continue growing in roles where I can apply AI and digital transformation to solve complex business problems and create measurable impact.
Machine Learning, Deep Learning, NLP, cloud computing, databases, DevOps.
Specialization in data analysis and Industry 4.0.
Erasmus at Luleå University of Technology, Sweden.
Consulting skills, problem analysis, business models, agile methods, business case definition, teamwork, design thinking, innovation projects.
Project management certification.
Azure certifications.
Built a production-ready multi-agent AI system enabling natural language data analysis for enterprise users. Designed stateful workflows using LangGraph, coordinated specialized agents for retrieval, analysis, visualization, and planning, implemented SQL plus vector search on LanceDB, and deployed via Docker and Gradio.
Developed and deployed scalable multi-agent AI systems for pharma into production using LangGraph, LangChain, Azure AI Services, AI Foundry, Semantic Kernel, Foundry SDK, AutoGen, and CrewAI. Led RAG-based AI solutions and managed the Generative AI asset repository on Azure DevOps with CI/CD and MLOps standards.
Led development of a Transformers-based AI tool for real-time customer feedback analysis using LLMs and NLP. Optimized BERT models to improve sentiment analysis, customer engagement, and decision-making.
Enhanced customer experience and business operations by leading a Generative AI proof of concept with LLMs, OpenAI API, and Azure. Created an MVP that reduced task completion time by 80% and improved productivity. Worked on DevOps and MLOps with Azure, CI/CD pipelines, and Docker.
Led Industry 4.0 initiatives using Python and IoT, achieving annual cost savings per manufacturing line and supporting predictive maintenance applications.
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