Architecture & engineering for AI and data platforms
I work with companies building something substantial: complete AI platforms, data infrastructure, critical software products, and complex internal tools — from architecture decisions to systems running in production.
Types of project
End-to-end AI platforms
LLM, RAG, and agent systems designed for production: architecture, evaluation, cost, reliability, and the product around the model.
Data infrastructure
Pipelines, streaming, validation, and data platforms that scale — the foundation every serious AI system stands on.
ML systems & MLOps
Reproducible training, deployment, monitoring, and retraining — the full operation that keeps models useful after launch.
Product & platform architecture
Service design, plugin systems, APIs, and the trade-offs that decide how far a product can grow. I also lead architecture decisions alongside your team.
Applied optimization
AutoML, evolutionary algorithms, forecasting, and scheduling — the specialty behind my open-source libraries, applied to real business problems.
AI strategy & design
Defining the AI strategy before writing code: where it actually fits, prioritized use cases, a roadmap, and the high-level architecture decisions that keep you from building the wrong thing.
How I work
- Architecture definition: assets, constraints, trade-offs, and a design your team can sustain.
- Phased construction: a system running in production early, with explicit metrics and criteria.
- Real handoff: documentation, recorded decisions, and a team able to operate and evolve the platform.
Evidence, not promises
The engineering I offer is published and verifiable: Ciaren, an open-core visual workflow builder; open-source libraries widely adopted by the community (sklearn-genetic-opt, PyWorkforce), with public documentation and releases; and years of building production ML systems for companies.
Frequently asked questions
Don’t see your question here? Reach out and we’ll talk through your specific case.
AI platforms, data infrastructure, production ML systems, complete software products, and complex internal tools. Also architecture leadership or review. I don’t take on one-off support work, small automations, or simple website builds.
Both. I can lead architecture decisions alongside your team, or design and build the complete platform end to end: data, models, services, and product. Most projects combine the two.
It’s all public: Ciaren (a visual workflow builder for data pipelines and ML), sklearn-genetic-opt and PyWorkforce (widely adopted libraries with public documentation and continuous releases), and a track record of production ML systems for companies like EPAM, Globant, Rappi, and Avianca.
Yes. I work with companies across Colombia and LATAM, and remotely with teams in other time zones. Most projects run fully remote, with synchronous working sessions whenever the team needs them.
With a conversation about the business goal and the current technical state. From there comes an architecture definition — assets, constraints, risks, and a concrete design — and a phased construction plan with explicit production criteria.