Chile
I build backend systems that hold up under pressure — distributed architectures, event-driven pipelines, and optimization services that have cut critical operation times from hours to minutes in production. 7 years working with Python and TypeScript microservices across IoT, SCADA, and logistics-adjacent domains. I've designed systems that ingest data from 1,000+ devices, modeled knowledge graphs from scratch, and migrated monoliths into reliable microservice networks. Beyond the code, I care about the team around it. I've introduced testing culture from zero, set code quality standards, and mentored junior engineers — because a system is only as reliable as the people maintaining it. Currently exploring opportunities as a Tech Lead or Staff Engineer where technical depth and engineering craft both matter. Languages & Frameworks: ‣ Python (FastAPI, SQLAlchemy) · TypeScript (NestJS, Next.js, Prisma) Databases: ‣ PostgreSQL · MySQL · InfluxDB · Redis · Neo4j · Memgraph Architecture & Systems: ‣ Microservices · Event-driven architecture · Outbox pattern · IoT / MQTT · SCADA Testing & Quality: ‣ Playwright · Gherkin / BDD · Unit testing · Code review AI-assisted Development: ‣ Structured LLM workflows · CLAUDE.md guidelines · AI code quality oversight
- Designed and implemented an event-driven architecture using the Outbox pattern for a private rental platform, ensuring reliable message delivery and data consistency across distributed services. - Built the project's first automated regression baseline: a full Gherkin + Playwright end-to-end test suite covering all core user flows. - Introduced unit testing from zero and reviewed 50+ PRs for a 2-person junior team, raising code quality and supporting developer growth toward mid-level. - Established structured AI-assisted development practices via CLAUDE.md guidelines, ensuring consistent quality oversight of AI-generated code across the team.
- Redesigned an underperforming microservice system into a queue-driven monorepo, eliminating RAM bottlenecks and DB connection exhaustion — reducing client KPI calculation time by 50%. - Built and deployed a mathematical optimization microservice (Python, FastAPI, OR-Tools, MySQL) that reduced critical operation times from hours to minutes for a key client. - Prototyped a client knowledge graph in Memgraph and Neo4j, designing the entity relationship model and ontology from scratch. - Defined development tooling standards and best practices that reduced code review comments by 30%, improving team maintainability and velocity.
- Built an MQTT ingestion microservice normalizing data from 1,000+ IoT devices across 3 device types, enabling optimized InfluxDB queries and a unified downstream API layer. - Led migration from a KPI monolith to a parallelized microservice network, increasing reliability from ~70% to 95%+ and cutting processing time from hours to under one hour.