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Freelance AI Architect | Enterprise Knowledge Graphs | Semantic Technologies | GenAI & ML Integrations
🔹 Why Knowledge Graphs + Semantic Tech + AI We’re entering an era where organizations need to go beyond isolated data pipelines and black-box models. They need living, explainable, interconnected knowledge. Not just more data. The convergence of semantic technologies, enterprise knowledge graphs, and applied AI offers a breakthrough path forward: - Semantic technologies bring meaning and structure to data, enabling machines to understand relationships, not just process records. - Knowledge graphs act as a unified knowledge layer, connecting data, logic, and context across the enterprise. - AI applications powered by these graphs become more explainable, adaptive, and integrated with real business semantics. This is how we move from brittle automation to intelligent systems that reason, learn, and adapt, grounded in the organization's actual knowledge. 🔹 I help organizations build Enterprise Knowledge Graphs that connect data, semantics, and AI, transforming scattered information into living knowledge that powers intelligent systems. Working at the intersection of semantic technologies, graph modeling, and applied AI, I design scalable architectures that bring meaning to data, enable explainable automation, and support strategic decision-making across the enterprise. Whether you're starting from scratch or scaling an existing initiative, I can support you in shaping the vision, designing the models, and making the key decisions that turn knowledge into a real competitive advantage. It's not just technical. it's not “just another IT project”, It's strategic, it’s a transformational program. 🔹 What I Bring ✅ Enterprise Knowledge Graph at Scale Not just PoCs. I help you design and implement production-ready knowledge graphs that become foundational assets in your data strategy. ✅ Semantic Modeling & Ontologies RDF/OWL, SPARQL, SHACL, and g
IE Business School
Executive MBA
January 1, 1998 – January 1, 1999
Universidad Politécnica de Madrid
Ingeniero Telecomunicaciones
January 1, 1987 – January 1, 1990
Freelance
Freelance Consultant | Enterprise Knowledge Graphs & AI | Semantic Data Architect
August 1, 2025 – Present
UL
Enterprise Knowledge Graph Architect
June 1, 2021 – August 1, 2025
Airbus Defence and Space
AI & Advanced Analytics - Technical Delivery Lead
January 1, 2019 – June 1, 2021
Madrid, Community of Madrid, Spain
AXA
Machine Learning Business Solutions Manager - EMEA - LATAM Region
January 1, 2016 – January 1, 2019
ING Bank España
Digital Banking Enterprise Architect & Data Engineering Lead
May 1, 2014 – January 1, 2016
Madrid Area, Spain
SOAIN Software Associates
Enterprise Architect
March 1, 2010 – April 1, 2014
CMC-GPM
Enterprise Architecture Practice Manager
April 1, 2009 – March 1, 2010
SOAIN Software Associates
PreSales Director, Enterprise Architect
May 1, 2007 – April 1, 2009
Contractor, Free Agent
BPM Consultant, Project Manager
January 1, 2005 – May 1, 2007
Aquantis
Founder & Managing Director
January 1, 2001 – January 1, 2005
Atos Origin
Telecommunications & Media Industry Manager
April 1, 2000 – January 1, 2001
Ericsson
Business Development Manager – New Operators
January 1, 1997 – April 1, 2000
Alcatel
Product Manager - HFC Solutions
July 1, 1990 – January 1, 1997
Machine Learning by Andrew Ng
Stanford University - Coursera
June 24, 2026 – Present
IBM Business Process Manager, BPM Application Development
IBM Authorized Prometric Testing Center
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's career trajectory shows a strong inclination towards innovation and strategic transformation, moving from traditional telecom roles to cutting-edge AI and semantic technologies. Their experience across various industries (Freelance, UL, Airbus, AXA, ING, Telco) and roles (architect, lead, manager, founder) demonstrates adaptability and a broad perspective, which are valuable for cultural fit in dynamic environments. The entrepreneurial background (Aquantis Founder) also suggests a proactive and results-oriented mindset. The target role of AI Engineer aligns with their recent focus on AI, NLP, and Knowledge Graphs, indicating a strong interest and relevant skill set.
Soft Skills & Operational Fit
The candidate's extensive experience in leadership roles (Technical Delivery Lead, Business Solutions Manager, Enterprise Architect, Practice Manager) suggests strong soft skills in strategic planning, team leadership, stakeholder management, and business development. Their freelance consultant role further indicates autonomy, problem-solving, and client-facing communication abilities. The focus on transforming fragmented data ecosystems into semantic platforms aligns well with operational needs for robust, scalable AI infrastructure.