Available for new projects

Hi, I'm Diego De La Flor

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AI & Full Stack Developer

I transform complex problems into high-impact software using AI and modern architectures.

View projects GitHub
2+ Years of experience
3+ Progressive roles
4 Featured projects
100% Impact-driven

01. about

About me

Who I am, what I do, and the technologies I use to do it.

D

Diego De La Flor

AI & Full Stack Developer

Full Stack Developer with 2+ years of experience specializing in AI integration, intelligent automation, and cloud-native architectures. I design and build end-to-end systems: from IoT sensors and data pipelines to scalable REST APIs and reactive frontends. Passionate about reducing operational friction with applied machine learning and delivering measurable value in every sprint.

  • Location Lima, Peru
  • Education Software Engineering — UPC, Lima
  • Languages Spanish (native) · English (B1)
  • Availability Open to work — full-time / freelance

Courses & Certifications

  • Excel Specialist IDAT · 2023
  • Cybersecurity Analyst UPC · 2022
  • SQL for Data Science UPC · 2022

Tech stack

Backend
C# .NETNestJSSpring BootLaravelREST APIsMicroservicesNode.js
Frontend
ReactNext.jsAngularFlutterTypeScriptHTML5 / CSS3Responsive Design
AI & Data
PythonLLMsPrompt EngineeringRAGRandom ForestMachine LearningIoT / ESP32
Databases
SQL ServerPostgreSQLMySQLMongoDBFirebaseAzure DB
DevOps & Cloud
DockerGitHub ActionsAWSAzureCI/CDJenkinsGit
Methodology
SCRUMJiraConfluenceClean ArchitectureDDD

02. experience

Experience

Professional journey and the problems I have solved in production.

  1. Current

    AI Developer

    Mando HR

    Feb 2026 – Present
    • Developed an advanced automation tool that analyzes the web DOM to automatically generate JSON component structures and Cypress End-to-End test scripts.
    • Engineered an AI-powered test generation system using RAG to integrate OpenAI API with Jira and Confluence achieving a 70.9% reduction in manual effort.
    • Built a cross-platform desktop application using Electron and React to record user interactions and transform them into reusable testing artifacts.
    • Accelerated development velocity through prompt engineering and AI-assisted code generation to streamline the delivery of complex software features.
    • Conducted technical analysis and code reviews for Laravel modules ensuring high quality standards and seamless integration within the existing ecosystem.
    PythonLLMsAzure DBPrompt EngineeringREST APIsDockerAPI AnthropicAPI OpenAIRAGJira APIGCP

  2. Full Stack Developer

    Mando HR

    Jan 2025 – Jan 2026
    • Developed scalable functionalities using Laravel and NestJS for the backend, integrated with dynamic interfaces built in Angular (Ant Design) and React + Vite.
    • Drove continuous improvement of legacy applications, implementing design patterns to enhance maintainability and overall software performance.
    • Architected and optimized SQL and NoSQL database queries, ensuring high-speed response times and structured data management.
    • Developed and integrated robust APIs, facilitating seamless interoperability between microservices and PHP/Laravel applications.
    • Optimized bulk data import engines, achieving a significant reduction in execution times while ensuring data integrity and preventing duplicates.
    ReactNext.jsC#.NETJWTAzure ADViteTypeScript

  3. QA Trainee

    Mando HR

    Sep 2023 – Dec 2024
    • Ensured the quality and consistency of PHP-based backend services by implementing comprehensive test suites in Postman for API contract validation.
    • Maximized system performance through detailed metric analysis using Apache JMeter, effectively mitigating service downtime risks under high-demand scenarios.
    • Guaranteed 100% test coverage for critical requirements across web and mobile platforms, streamlining defect documentation and cross-team communication.
    • Reduced visual and functional inconsistencies by standardizing global compatibility testing with BrowserStack, covering a wide range of browsers and operating systems.
    JMeterBrowserStackAPI testingPerformance testingPostmanNewmanAgile methodologies

03. projects

Featured Projects

Systems I designed and built end-to-end, from architecture to production.

Public 1 project — code available
Private 3 projects — under NDA / proprietary
Public

Legacy-to-Modern Architect

Feb 2026

Problem

Legacy monolithic applications with accumulated technical debt, slow deployment times, and high friction for incorporating new features.

Architectural solution

Progressive migration architecture from monolith to microservices using strangler-fig pattern. CI/CD pipeline with GitHub Actions, Docker containers, and deployment on AWS/Azure. Incremental refactoring with feature flags for zero-downtime migration.

Impact & Value

  • 70% reduction in deployment time
  • Decoupled architecture ready to scale horizontally
  • Technical documentation of replicable patterns

Technologies

Node.jsDockerGitHub ActionsAWSAzureMicroservicesReactTypeScript
Private

Agricultural Recommendation System — Coffee

Aug 2024 – Dec 2025

Problem

Coffee farmers lack personalized, data-driven guidance to optimize yield and crop quality based on real environmental conditions.

Architectural solution

Dual backend system: Spring Boot for local IoT sensor data processing and .NET (Azure) for cloud logic. Data pipeline from ESP32 sensors (humidity, NPK, rain) to a trained Random Forest model for contextual recommendations. REST APIs consumed by a frontend application.

Impact & Value

  • ML engine with Random Forest for real-time recommendations
  • Integration of 4 IoT sensor types in production
  • Dual local/cloud backend for offline resilience
  • Decoupled REST APIs consumed by multiple frontends

Technologies

Spring BootJava.NETAzurePythonRandom ForestESP32Raspberry PiIoTSQL ServerREST APIs
Private

RAG-Powered Test Generator

Jan 2026 – Present

Problem

Manual creation of test cases from user stories in Jira and Confluence consumed ~50 hours per sprint, creating QA bottlenecks.

Architectural solution

RAG (Retrieval-Augmented Generation) system that ingests and contextualizes technical documentation from Jira and Confluence. Orchestrated with Node.js and the Anthropic API, it automatically generates structured test cases and exports them as Cypress code and Google Sheets records.

Impact & Value

  • 70.9% reduction in test creation time (50h → 14h per sprint)
  • Automated traceability from requirement to E2E test

Technologies

Node.jsAnthropic APIRAGJira APIGoogle SheetsCypress
Private

DOM Capture & Test Generator

Feb 2026

Problem

Building E2E test scripts required manual, repetitive DOM inspection to extract robust selectors, slowing down test coverage for new features.

Architectural solution

Desktop application built with Electron, React, and Vite that visually captures the DOM state in real-time during user navigation. Automatically generates JSON component mappings (Page Object Model) and produces reusable E2E tests ready for Cypress.

Impact & Value

  • Radical acceleration in coding and maintaining E2E tests
  • Standardized selectors, reducing test suite fragility

Technologies

ElectronReactViteTypeScriptCypressDOM Analysis
See all my repositories on GitHub

04. contact

Let's work together

Do you have an ambitious project or a position where you need AI and modern architectures? I am available for conversations.

Send me a message

I reply within 24h. Tell me about the technical challenge or opportunity and we will see if there is a fit.

diegoalonso139@gmail.com
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