Spain
I am a T-shaped strategist operating at the intersection of Process Engineering (Lean/BPM), Agentic AI, and Regulatory Compliance (EU AI Act / ISO 42001). With a 247.5 ECTS engineering foundation from IQS, I bridge Deep Tech delivery and C-suite risk concerns across the full AI lifecycle. ◼ SDLC-NATIVE GOVERNANCE My core focus is SDLC-native governance: designing architectures where risk controls, documentation, and compliance checks are embedded directly into the delivery pipeline. This enables teams to build and deploy AI systems that are scalable, auditable, and aligned with evolving regulation. ◼ R&D AND EXECUTIVE LEARNING Over the past several years, I have concentrated on advancing Responsible AI and governance through a mix of independent R&D, prototyping, and executive-level study. This work includes "Compliance-as-Code" concepts for recruitment workflows and decision-logging patterns, together with 40+ advanced programs in AI Governance, Strategy, and Deep Learning from leading institutions. ◼ INNOVATION BACKGROUND & OBJECTIVE Earlier in my career, I was recognized by the Repsol Foundation for applying Lean methodologies to address complex market gaps, reinforcing a bias toward measurable, experiment-driven improvement. I am now looking to bring this systems mindset and governance toolkit into a global consultancy, helping clients turn AI regulation into a practical engineering advantage. // Governance Log Status: Banner contains AI-generated typo ("COMPLLANCE"). Action: Retained as a production artifact. Reasoning: It demonstrates the "Tail Risk" of Agentic AI. The model handles 99% of the volume flawlessly, but the final 1% of edge cases carries 100% of the reputational risk. Governance exists to catch that critical 1%.
Independent consulting and R&D activity focused on Responsible AI (RAI) governance frameworks, agentic systems, and regulatory alignment (EU AI Act, ISO 42001). ► Responsible AI Governance & Strategy Designed SDLC-native governance frameworks to translate regulatory and risk requirements into technical criteria for AI systems. Operationalized algorithmic risk management with frameworks for risk classification, documentation standards, and auditability. Implemented Human-in-the-Loop (HITL) and dual-approval controls for high-impact decisions. Conducted benchmarking of publicly available enterprise governance models to validate approaches against industry standards, including: Microsoft: Responsible AI Standard BBVA: Banking-grade risk controls Deloitte: ISO-aligned methodologies ► Applied Technical Architecture Designed and developed agentic system prototypes and architectures (LangGraph + FastAPI) with supervision and state management for controlled execution. Designed governance-first ML pipelines embedding drift monitoring, fairness checks, and audit logging. Developed ToxiChain prototype, a blockchain-backed system for immutable decision-logging and content detection. Performed data stack benchmarking (Pandas vs. Polars) to drive engineering decisions. ► Executive Specialization Completed 40+ certifications, including Oxford (AI Governance) and Stanford (Advanced Algorithms). Designed an AI-assisted curriculum framework to curate a learning path aligned with the Enterprise Responsible AI Architect role.
User Onboarding and system configuration Avaya Cloud office and Azure I 've successfully onboarded and trained high level users usually CEO s and Heads of IT by configuring and fine tunning systems to meet their specific needs NLP Fine Tunning Spanish: I specialize in optimize Natural Language Processing models to enhance user experience and improve system accuracy. Stakeholder Management I am skilled bridging the gap between technical teams and stakeholders, ensuring product align with company objectives.