Short bio · ~50 words
Daniel Gómez Domínguez is an AI Systems Architect directing agentic stacks on LLMs — specialising in retrieval, multimodal infra, generative rollout, and cost-aware inference.
Speaking & press
Speaker kit for briefings, panels, and technical keynotes — bios, topics, and assets.
Bios
Medium bio · ~120 words
Daniel directs AI programmes where agentic tooling must survive production constraints. He leads architecture for LLM-backed acquisition systems, multimodal embeddings, reinforcement-flavoured recommenders and safety-sensitive fraud workloads. Earlier he spent six years modelling brain rhythms inside CSIC before moving through classical ML deployments and frontier generative workloads.
Long bio · ~280 words
Daniel splits his craft between BillionHands-level agent design and multimodal retrieval platforms — marrying neuroscientific rigor with ruthless product pacing. Highlights include multimodal embeddings co-existing with reinforcement-style recsys across consumer search, antifraud GPT detectors, multimodal garment recognisers resilient to showroom-quality shifts, RL trading experiments for banks, electrophysiology workloads at Cajal-scale, plus a parallel career translating technical depth for national press and flagship YouTube documentaries. Comfortable presenting to CFOs down to infra ICs — multilingual, Madrid-based but EU-remote friendly.
Suggested topics
- Designing agent memory you'll trust in prod
- Multimodal RAG sans infinite spend
- Reinforcement-informed recommenders vs pure LLMs
- From CSIC rigs to hyperscale infra — lessons in rigor vs velocity
- Fraud & synthetic-media detection narratives for banks and marketplaces
Headshots
B&W photo for editorial use. If you need a color or higher-resolution version, drop me a note.
Talks / sessions
- Agentic architectures for regulated knowledge retrieval — Invite-only CTO roundtables · Planned
- Operationalizing multimodal embeddings at catalogue scale — Portfolio internal tech weeks · Delivered