Resume

Juan David Leon Castillo

AI-Augmented Software Architect

Software architect and engineering leader with experience designing scalable systems, developer platforms, and engineering workflows across backend, infrastructure, and AI-augmented development contexts. Strong focus on architecture, productivity, automation, and practical technical leadership.

contact@juanleon.dev

Bogota, Colombia

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Core Expertise

Architecture, delivery, and developer productivity capabilities.

Grouped to support quick scanning by recruiters and technical stakeholders.

Software Architecture

Distributed systems • API design • Microservices • Modular design • Technical strategy

Backend Engineering

Java • Kotlin • Python • REST APIs • GraphQL • Service integration

Frontend and Product Engineering

React • Next.js • TypeScript • Tailwind CSS • UI architecture

DevOps and Infrastructure

Docker • Kubernetes • Rancher • CI/CD • Deployment automation

AI-Augmented Engineering

Local LLM workflows • Coding agents • Spec-driven development • AI documentation • Developer tooling

Data and Persistence

PostgreSQL • SQLite • Integration patterns • Schema design • Application data modeling

Experience

Recent role history and scope.

Concise bullets prioritize system design, leadership, platform work, and engineering improvements.

Tech Manager / Engineering Leadership

Confidential / Enterprise Engineering Context • Hybrid

Current / Recent

Leading engineering initiatives with a focus on technical execution, delivery quality, team coordination, and architecture-aligned decision-making.

Coordinated engineering work across delivery streams while preserving architectural coherence and practical execution standards.
Supported technical decisions spanning backend services, tooling, developer workflows, and delivery enablement.
Improved engineering throughput through stronger specifications, process clarity, and reusable implementation patterns.

Senior Software Engineer / Architect-Level Delivery

Enterprise Platforms and Product Teams • Colombia

Worked across backend systems, integration-heavy platforms, infrastructure workflows, and internal tooling with a strong systems mindset.

Designed and delivered backend solutions for integration-heavy environments with an emphasis on maintainability and reliability.
Contributed to infrastructure and platform efforts including automation, Kubernetes-oriented environments, and developer support tooling.
Bridged architecture concerns with implementation detail to keep delivery grounded in practical engineering outcomes.

AI Workflow and Developer Productivity Builder

Independent and Experimental Work • Remote

Ongoing

Exploring local AI, agentic workflows, documentation systems, and structured engineering processes that improve software delivery.

Built experimental systems around local LLMs, coding agents, and privacy-aware developer AI workflows.
Developed specification-driven practices that strengthen implementation alignment, reproducibility, and engineering communication.
Created portfolio-ready technical concepts that connect AI experimentation to practical platform and architecture outcomes.

Selected Projects

Projects that reinforce architecture depth and AI workflow experimentation.

A shortlist of representative systems and frameworks aligned to the positioning of the site.

MCP Test Impact Analysis System

A local-first engineering tool that analyzes code changes and predicts likely test impact without requiring external AI infrastructure.

Technical focus: Reduce unnecessary test execution while keeping engineering data local, secure, and operationally simple.

Spec-Driven Engineering Framework

A structured engineering workflow that turns specification artifacts into implementation guidance, architecture alignment, and project consistency.

Technical focus: Create a reproducible path from requirements to delivery without losing technical rigor or documentation quality.

Local LLM Developer Platform

An experimental platform for integrating local LLMs into day-to-day software development without sending sensitive project context to external services.

Technical focus: Balance privacy, speed, and developer experience when bringing AI assistance into real engineering workflows.

Blockchain Market Data ETL Platform

A data processing workflow for collecting, transforming, and analyzing blockchain and market data through ETL pipelines designed for reporting, analytics, and operational use.

Technical focus: Turn fragmented blockchain and market sources into structured, queryable datasets that can support product decisions and downstream analysis.