×
Eduardo Haraguchi

Eduardo Haraguchi

Software Engineer | Backend & AI/ML Specialist

São José dos Campos, State of São Paulo, BR
+55 61 99647-9262
Portuguese, English

Background


About

About

Highly motivated and adaptable Mechanical Engineering student at ITA with a deep passion for designing and implementing scalable backend systems, advanced mathematics, and practical Artificial Intelligence/Machine Learning (AI/ML) solutions. Proven ability to quickly learn and apply complex theoretical concepts to real-world engineering problems. Currently building AI agents as a Software Engineer, with a strong focus on robust backend development and prompt engineering. Self-driven with impactful personal projects in distributed systems, full-stack AI applications, and data analysis. Seeking challenging backend or AI/ML engineering roles in innovative tech companies or dynamic remote startups where I can leverage my specialized skill set, drive continuous learning, and contribute to cutting-edge solutions at scale.

Work Experience

Work Experience

  • Software Engineer (Backend & AI Focus), Brendi Tech

    Dec, 2023 - Present

    Designing and developing AI agents for food delivery chatbots, with primary responsibility for backend architecture, prompt engineering, and system scalability.

    • Architected and implemented scalable conversational AI backend services using Node.js and TypeScript for WhatsApp-based chatbots.

    • Managed and optimized critical backend infrastructure leveraging Google Cloud Platform (GCP), Firebase, and Firestore to ensure high availability and performance.

    • Designed and integrated robust APIs with third-party services, managing data persistence across MongoDB and BigQuery.

    • Engineered and fine-tuned AI agent responses through advanced prompt engineering techniques, resulting in [quantifiable improvement, e.g., 'X% reduction in misinterpretations' or 'Y% increase in successful order completions'].

    • Contributed to data engineering initiatives to support AI model development and performance monitoring, analyzing [specific data metrics, e.g., 'user interaction logs for model retraining'].

Projects Experience

Projects Experience

  • LLM Study Assistant (Full-stack AI Application)

    - Present

    Developed a comprehensive open-source LLM-powered study assistant to enhance learning and knowledge retention, leveraging RAG and Spaced Repetition Systems.

    • Designed and implemented a full-stack web application (React, Node.js) featuring an interactive chat interface for educational purposes.

    • Integrated with OpenRouter and Ollama to leverage various open-source Large Language Models (LLMs) and embedding models for diverse functionalities.

    • Engineered a robust Retrieval Augmented Generation (RAG) system to enable precise querying and summarization of uploaded PDF documents, achieving [quantifiable metric, e.g., 'X% retrieval accuracy' or 'Y% reduction in hallucinated responses'].

    • Implemented a Spaced Repetition System (SRS) algorithm to generate personalized review questions from extracted notes, reportedly improving user retention by [quantifiable metric, e.g., 'anecdotal Z% improvement in test scores'].

    • Managed database schema and operations using SQLite, ensuring efficient data storage and retrieval for user interactions and notes.

  • Concurrent Text Editor (Distributed Systems & Backend Exploration)

    - Present

    Designing a distributed concurrent text editor to explore various programming paradigms, concurrency models, and distributed systems concepts.

    • Implemented backend services in Go and Erlang, focusing on efficient concurrency and inter-service communication (e.g., [specific protocol or method used]).

    • Explored functional programming paradigms with an in-progress Haskell service for advanced state management and fault tolerance.

    • Successfully containerized the entire application using Docker and deployed to a remote server for testing distributed functionality and scalability up to [number of concurrent connections/users tested].

    • Gained hands-on experience with state synchronization, fault tolerance, and design patterns for robust distributed systems.

Skills

Skills

  • Programming Languages

    TypeScript

    Node.js

    Python

    Go

    Erlang

    Haskell (learning)

    SQL

    MATLAB

  • Backend Development

    Express.js

    Backend Development

    Microservices Architecture

    Distributed Systems Design

    API Design (RESTful)

    Data Modeling

  • AI & Machine Learning

    Prompt Engineering

    Large Language Models (LLMs)

    Retrieval Augmented Generation (RAG)

    Convolutional Neural Networks (CNNs)

    Anomaly Detection

    Kalman Filters

    Koopman Operators

    Spaced Repetition Systems (SRS)

    TensorFlow/Keras

    NumPy

    Pandas

  • Cloud Platforms & Databases

    Google Cloud Platform (GCP)

    Firebase

    Firestore

    Docker

    MongoDB

    PostgreSQL

    SQLite

    BigQuery

  • Tools & Technologies

    Git

    Postman

    OpenRouter

    Ollama

    Kanban

Education

Education

  • Mechanical Engineering, Bachelor of Engineering, Instituto Tecnológico de Aeronáutica (ITA)

    Jan, 2021 - Dec, 2025

    Advanced Mathematics & Computer Science Optionals (GPA 8.8/10): Real Analysis, Functional Analysis, Ring Theory, Computational Linear Algebra, Discrete Mathematics and Cryptography, Algorithms and Complexity

    Relevant Core Coursework: Classical Control Systems, Thermodynamics, Fluid Mechanics, Solid Mechanics

    Undergraduate Thesis (in progress): Kalman Filtering and Koopman Operators for System Estimation and Control (focus on heavy theoretical and mathematical foundations, including self-study of Measure and Probability Theory). Aiming to submit [paper title/details] by [Target Date].

Volunteer Work

Volunteer Work

  • Undergraduate Researcher (AI/ML), ITA (Instituto Tecnológico de Aeronáutica)

    Jan, 2022 - Dec, 2022

    Explored the application of Convolutional Neural Networks (CNNs) for anomaly detection in industrial datasets.

    • Developed foundational expertise in Python for machine learning tasks, including data manipulation with NumPy and Pandas.

    • Gained practical understanding of CNN architectures and their utility in unsupervised learning contexts.

    • Researched and applied data preprocessing and feature engineering techniques essential for anomaly detection algorithms.

Interests

Interests

  • Artificial Intelligence & Machine Learning

    Deep LearningNatural Language ProcessingGenerative AIControl Systems TheoryMathematical ModelingReinforcement Learning
  • Backend Engineering

    Scalable SystemsDistributed ComputingConcurrencyPerformance OptimizationAPI DevelopmentSystem Design
  • Mathematics

    Real AnalysisFunctional AnalysisLinear AlgebraProbability TheoryStochastic ProcessesGraph TheoryNumerical Methods
  • Programming Paradigms

    Functional ProgrammingConcurrent ProgrammingObject-Oriented Programming
  • Programming Languages Design

    ErlangHaskellGo