Francisco Manuel Olmedo Cortés
AI Solutions Architect & Lead Backend Engineer
Córdoba, Andalucía, España
About
Physicist and AI Solutions Architect specialized in Generative AI and Backend engineering. I design and build production-ready systems (RAG, Autonomous Agents, LLM orchestration) that solve real business problems, cutting through the hype to focus on operational efficiency. I lead the full software lifecycle, applying Clean Architecture to ensure maintainable, scalable, and low-latency systems. My background in physics drives a first-principles, systems-oriented approach to complex technical decisions.
Experience
BlakIA
Co-founder & Lead Technical Architect
Córdoba, Andalucía, España
- Designed and implemented B2B Generative AI systems from scratch, focusing on RAG pipelines and Agentic AI for enterprise workflow automation.
- Owned core architecture decisions, applying Lean methodologies and Clean Architecture to keep systems robust, scalable, and with minimal technical debt.
- Delivered high-concurrency deployments in production, including an official chatbot handling 100,000+ interactions in a week with peaks above 10,000 users.
Hagalink
Chief Data Scientist (CDS) / Lead AI Engineer
Córdoba, Andalucía, España
- Lead the end-to-end design and implementation of AI/ML systems, translating ambiguous client requirements into scalable backend architectures.
- Build robust APIs in Python, managing vector databases and LLM orchestration in production environments.
- Act as the technical bridge with clients, explaining architectural trade-offs across accuracy, computational cost, and latency.
Universidad de Córdoba (Confidential Project)
Scientific Software Architect / Researcher
Córdoba, Andalucía, España
- Refactored a highly complex legacy scientific simulator (ray tracing), applying Clean Architecture principles to ensure scalability and maintainability.
- Designed and implemented an optimizer based on Genetic Algorithms for the automated design of complex physical structures.
- Led the technical standardization of the codebase.
IDENER.AI
R&D Software Engineer
Sevilla, Andalucía, España
- Applied deep learning models for time series forecasting to optimize energy production predictions.
- Bridged the gap between theoretical scientific requirements and efficient, functional code in a fast-paced R&D environment.
CIEMAT / Universidad de Córdoba
AI Researcher & Scientific Developer
Madrid / Córdoba, España
- Developed a physical simulator based on the numerical resolution of differential equations (Runge-Kutta) in Python, deployed as a web tool via Streamlit.
- Synthetic Data Generation: Utilized the simulator as an 'Oracle' to generate high-precision datasets for Deep Learning.
- Designed and trained Fully-Connected Neural Networks for kinetic parameter assessment, leading to a peer-reviewed publication.
- I taught an introductory course on Python for scientific computing and data science.
Education
Universidad de Córdoba / CIEMAT Environment
Ph.D. Candidate (Doctorando) in Physics / Applied AI
Universidad de Córdoba
Master in Physical Technology: Research and Applications
Universidad de Córdoba
Bachelor (Degree) in Physics
Technical Skills
Backend & Architecture
- Clean Architecture
- Python
- FastAPI
- typescript
- nestjs
- RESTful APIs
- System Design
- database architecture
AI & Data Engineering
- Generative AI
- Agentic AI
- RAG Pipelines
- LLMs (LangChain/LlamaIndex)
- Vector Databases (Qdrant, Weaviate)
- Synthetic Data Generation
- Neural Networks
Infrastructure & Ops
- Linux
- Docker
- Git
- CI/CD
- Hetzner
- GCP
Core Physics & Math
- Mathematical Modeling
- Statistical Optimization
- Genetic Algorithms
- Monte Carlo Methods
Productivity
- Neovim/Vim
- TUI Environments
- High-speed Terminal Workflows
- AI asisted programming
- opencode
Languages
Spanish
Native
English
Professional Working Proficiency (B2)