Product Manager and Builder. Berlin, Madrid.
Eight years building products at the intersection of growth, AI, and international scale.
My focus is on making AI agents and GenAI workflows actually work for Growth teams — not as prototypes, but as deployed systems that change how a business operates.
AI Agent Solutions — end-to-end architecture for customer service automation, product discovery, inventory optimization, and merchandising. Live deployments, not demos.
RAG and Intelligent Retrieval — connecting internal data (product catalogs, docs, ticket history) to LLMs that can reason over it. The technical part is not the hard part. Getting organizations to trust and use the output is.
Market-Ready Accelerators — pre-built frameworks built for the clone-customize-run pattern. Shopify and e-commerce teams ship faster with templates that have already solved the integration layer.
Implementation and Governance — workflows for AI integration, monitoring, LLM evaluation, and risk management. The EU AI Act is starting to separate companies that shipped AI features from companies that built the compliance and safety layer around them. Most teams did the first part. The second part is still open work.
Upskilling and Enablement — business-friendly guides and crash courses for retail and growth teams. Demystifying LLMs, RAG, and agent architectures for people who make product decisions but don't write code.
- Voice AI agent deployed across 20+ countries: IVR, speech-to-text, NLP classification, escalation logic for non-technical field staff
- LLM validation platform: guardrails against hallucination, humanitarian data governance compliance, adoption toolkits for field teams who had no prior AI exposure
- Automated reporting pipeline replacing 40+ hours of manual work per month
JobQuest — Automated job application pipeline. Scrapes job postings, runs two-stage LLM tailoring (analysis brief then LaTeX generation), ATS keyword analysis, PDF compilation, Notion tracker entry. Multi-provider LLM fallback (Gemini, DeepSeek, OpenRouter). 9-step pipeline.
Two types of AI PMs are emerging from this wave. The ones who shipped features. The ones who built the system around the features. The gap between them compounds every quarter.