Due to NDAs and corporate policies, the vast majority of my professional-grade code resides in private repositories. The projects showcased here are primarily my academic and personal side-projects where I experiment, build, and deploy end-to-end systems from scratch.

• Enterprise AI Product Ownership (Orange-Door.com): Leading the product vision and technical governance for one of the largest Agentforce implementations globally (São Paulo's Poupatempo), impacting millions of citizens. Acting as the strategic bridge between world-class Salesforce teams, internal experts, and C-suite executives to ensure AI systems translate into immediate business value.

• Principal AI Strategy (GETTER S.A.): Spearheading the technical and architectural strategy for a Top 10 Industry 5.0 startup and South Summit Finalist (Top 50 out of 2,500+ global startups). Architecting multi-agentic and machine learning systems while aligning elite engineering with global business development and high-stakes enterprise contracts.

• Enterprise AI Architecture (VivaTerra Ventures): Orchestrating the technical blueprint, product, and data science strategy for a disruptive stealth startup. Designing hyper-scale, autonomous, multi-modal data pipelines utilizing SOTA Google infrastructure to translate complex biological realities into deterministic predictive models.

• Sovereign Data Ecosystems (Embrapa/ABCGIL): Architected the "Sovereign Bio-Graph," moving national genomic assets to air-gapped HPC infrastructure across 10+ countries.

• Neuro-Symbolic Breakthrough (FrameNet BR): Engineered a hybrid AI system fusing Vision Transformers with linguistic logic, achieving a 6x performance increase in semantic reasoning.

• 1st Place Winner - Reply Enterprise Challenge (FIAP NEXT 2025): Solo-architected a production-grade Agentic platform for predictive maintenance, reducing downtime by 40%.

• Global R&D Leadership: Orchestrated 3 international engineering cohorts at SuperDataScience, deploying full-stack financial intelligence and healthcare AI systems.

Operating at the intersection of AI, Solutions Architecture, Data Governance, C-Level Strategy, and Business Value, designing the infrastructure and technology of the next economic era.

As a Fractional AI Solutions Architect, I partner with disruptive startups and global enterprises to design and govern safe, state-of-the-art AI ecosystems that drive massive market ROI. I bridge the gap between deep R&D and the boardroom, translating complex data physics into scalable B2B revenue.

• AI Technical Product Owner @ Orange-Door.com: Leading the product lifecycle, Agile orchestration, and technical governance for the largest global Salesforce Agentforce implementation. Acting as the ultimate technical gatekeeper for architectural liability (ADRs) and UX/functional sign-offs.
• Principal AI Strategist @ GETTER S.A.: Driving the technical architecture and global pre-sales strategy for a Top 10 Industry 5.0 startup. Architecting complex multi-agentic infrastructures while ensuring enterprise data security and measurable ROI for global clients.
• Principal AI & Product Architect @ VivaTerra Ventures: Leading the design of global-scale, multi-modal data pipelines and the core "operating system" for a disruptive startup, translating highly complex biological data into high-fidelity digital assets.
• Enterprise Data Strategy @ Embrapa: Architected the digital foundations for international genomic improvement programs across 10+ countries, bridging the gap between PhD researchers and mission-critical business KPIs.

• Agentic AI Research @ UFJF (M.Sc. CS): Researching Cognitive Multi-Agent Systems (MAS) for autonomous decision-making and semantic interoperability in heterogeneous environments.
• Award-Winning Systems: Solo-architected the 1st place winner of the Reply Enterprise Challenge (FIAP NEXT 2025)—a production-grade platform for predictive maintenance.

AI Technical Product Owner | Orange-Door.com | Remote (Miami, FL) | Mar 2026 - Present

Operating at the intersection of business strategy and advanced AI engineering. Working in direct conjunction with an internal expert team and a world-class Salesforce team, I am currently working on the largest Salesforce Agentforce implementation globally for São Paulo's Poupatempo platform—architecting agentic AI systems designed to impact millions of citizens.

• Enterprise Product Ownership & Agile Orchestration: Directing the product lifecycle, backlog refinement, and sprint planning. Translating abstract business objectives into rigorous technical specifications and actionable epics.
• Cross-Functional Leadership & Stakeholder Alignment: Serving as the central axis across Discovery with stakeholders, architectural stages with Salesforce experts, and engineering development, bridging executive expectations and technical reality.
• Technical Governance & Liability Shielding: Instituting strict Architecture Decision Records (ADRs) to audit global partner directives, ensuring absolute compliance and isolating corporate liability in mission-critical deployments.
• AI Systems Architecture & Engineering Oversight: Advising on hybrid Multi-Agent Systems (MAS) and Agentforce architectures. Conducting daily technical and code reviews to guarantee top-tier software quality.
• Functional Authority & UX Validation: Holding final approval over functional specifications, UX journey mapping, and prototyping to match client expectations and executive ROI.

Key Areas: Agentic AI AI Architecture Salesforce Agentforce Enterprise Product Ownership Technical Governance Multi-Agent Systems

Principal AI Strategist | GETTER S.A. | Remote (Manaus, AM) | Mar 2026 - Present

Spearheading the technical and architectural strategy to revolutionize the Industry 5.0 sector through advanced AI, machine learning, and multi-agent systems. GETTER is recognized as a Top 10 startup in Industry 5.0 and a South Summit Finalist. I act as the critical nexus between high-stakes business development and elite engineering.

• Global Business Development & Pre-Sales Architecture: Drafting, refining, and validating high-stakes business proposals and executive pitches for large-scale enterprise contracts.
• AI Systems Architecture & Tech Governance: Architecting complex system designs and agentic infrastructures. Conducting rigorous technical reviews to ensure scalable, secure, and SOTA engineering standards.
• Technical Consulting & Strategic Prioritization: Advising the internal engineering ecosystem on development priorities and tech stack choices to optimize output for measurable ROI.
• Security & Risk Mitigation: Conducting rigorous data security auditing and technical risk mitigation at an enterprise scale for industrial clients.
• Executive Leadership & Organizational Alignment: Interfacing seamlessly with strategic partners, product managers, and the CEO to translate visionary goals into industry-defining automation.

Key Areas: Agentic AI Industry 5.0 Strategic Communications System Architecture Pre-Sales Architecture Tech Governance

Principal AI & Product Architect | VivaTerra Ventures | Remote (São Paulo, SP) | Mar 2026 - Present

Orchestrating the technical blueprint, product, and data science strategy for a disruptive stealth startup. Designing a global validation protocol at the intersection of AI, big data, and complex system modeling, leveraging state-of-the-art Google infrastructure.

• Enterprise AI Architecture: Conceiving the core "operating system" for large-scale AI. Architecting autonomous, multi-modal AI pipelines to ingest decentralized data streams into deterministic predictive models.
• Hyper-Scale Data Infrastructure: Designing advanced cloud-native architectures and high-performance computing strategies for processing massive, fragmented datasets with low-latency scalability.
• Applied Data Science & Systemic Modeling: Directing ML, Deep Learning, and MLOps initiatives to translate complex biological/physical realities into digital assets, integrating strict scientific constraints.
• Executive Product Strategy & Stakeholder Management: Serving as the nexus between scientific research, engineering execution, and institutional stakeholders (VCs, C-Suite), translating technical rigor into aggressive business KPIs.

Key Areas: Enterprise AI Architecture Hyper-Scale Data Infrastructure Systemic Modeling Applied Data Science MLOps

Data Manager: Strategy & Innovation | Embrapa/ABCGIL | Juiz de Fora, MG | Nov 2025 - Apr 2026

• Sovereign AI & LLMOps: Architected the "Sovereign Bio-Graph," moving national genomic assets to air-gapped high-performance computing, and modernized legacy pipelines by implementing state-of-the-art LLMOps and automated workflows.
• Global R&D Leadership: Bridged the gap between PhD researchers, world-class laboratory partners (Zoetis, Neogen), and industry-leading associations (ABCGIL), aligning complex genomic R&D with business KPIs across 10+ countries.
• Enterprise Data Engineering: Engineered robust ETL pipelines (Python, Pandas, Linux) and managed hybrid database solutions using PostgreSQL (Relational) and Neo4j (Graph) to ingest and standardize complex genomic structures.

Key Areas: Sovereign AI LLMOps Data Engineering Graph Databases ETL Pipelines Neo4j PostgreSQL

AI Researcher/Engineer (Neuro-Symbolic Architecture) | FrameNet Brasil / UFJF | Juiz de Fora, MG | Oct 2025 - Mar 2026

• Architectural Innovation (Project ReINVenTA): Led the engineering of a Hybrid Neuro-Symbolic System under the supervision of PhD researchers. Fused visual perception with structured linguistic logic to solve critical data quality issues (noisy labels) and scarcity constraints.
• SOTA Performance: Achieved a 6x improvement in multi-label classification accuracy, transforming a failing baseline into a robust model capable of abstract semantic reasoning.
• Advanced Tech Stack: Engineered end-to-end multi-modal solutions utilizing PyTorch, OpenAI CLIP (ViT-B/32), YOLOv8, and Vision Transformers (ViT), applying techniques like Asymmetric Loss (ASL) and Zero-Shot Learning in an NVIDIA A30 GPU optimized environment.

Key Areas: Neuro-Symbolic AI Computer Vision PyTorch Hugging Face Zero-Shot Learning

Project Lead: AI/ML Engineering & Data Science | SuperDataScience | *Remote | Jun 2025 - January 2026

• Agentic AI Leadership: Architecting "FinResearch AI", a multi-agent system using CrewAI to automate institutional financial research, pivoting teams from static notebooks to production-grade orchestration.
• Predictive ML Platforms: Delivered full-stack healthcare (GlucoTrack) and HR analytics (MLPayGrade) platforms using Deep Learning, Model Explainability, and Tabular Embeddings.
• Global Team Management: Orchestrating the full lifecycle for diverse international cohorts, aligning KPIs, conducting 1x1 mentorship, and enforcing software engineering best practices for scalable deployment.

Key Areas: Agentic AI Multi-Agent Systems CrewAI Technical Leadership LLMs RAG Full-Stack ML

Data Engineer (R&D) | Embrapa Gado de Leite | Juiz de Fora, MG | Sep 2025 - Nov 2025

• Increased performance by 87% of genomic queries by migrating from PostgreSQL to Neo4j.
• Architected a scalable bioinformatics fullstack pipeline for genomic analysis (Docker, Nextflow, FastAPI).
• Optimized project presentations for stakeholders and executives responsible for laboratory budget and resources.

Key Areas: Genomics Bioinformatics Data Engineering Neo4j

AI Trainer (LLM Systems via RLHF) | Outlier | Remote | Nov 2024 - Sep 2025

• Developed technical content to align Large Language Models (OpenAI, Meta, Anthropic), increasing model efficiency by 64% via RLHF in collaboration with technical teams.

Key Areas: RLHF Model Alignment AI Safety LLMs Quality Assurance

Data Analyst (Ecological Impact) | Impaakt | Remote | Feb 2022 - Oct 2024

• Delivered 500+ data-driven ecological impact reports that influenced ESG (Environmental, Social, and Governance) ratings used by investment firms.

Key Areas: Environmental Science Sustainability Analysis Data Analysis Process Optimization AI Integration Impact Assessment

Research Assistant | Georgia State University | Atlanta, GA | Feb 2019 - Feb 2020

• Increased research productivity by 84% by automating data collection and analysis workflows using Python.

Key Areas: Cognitive Sciences Philosophy of Mind Psychology Behavioral Analysis Research Methodology Data Analysis Data Science Python

Master of Science (M.Sc.) - Computer Science | Universidade Federal de Juiz de Fora (UFJF) | 2026 - 2028 (expected)

• Research Focus: Architecting Cognitive Multi-Agent Systems (MAS), semantic interoperability (Ontologies) in heterogeneous data, and autonomous decision-making based on Green AI.
• Key Graduate Coursework: Intelligent Agents • Autonomous Software Systems • Artificial Intelligence in Software Engineering • Machine Learning • Applied Intelligent Systems.
• Academic Excellence: Admitted with a 91.25 score on the Scientific Research Project defense.

Bachelor of Technology (Technologist Degree) - AI Systems & Machine Learning | FIAP | 2024 - 2026

Key Areas: AI Systems Architecture Machine Learning Engineering MLOps Edge AI IoT Development Software Engineering Data Engineering Cybersecurity Cloud Operations

Academic Excellence: GPA 4.0

Bachelor of Science - Biological Sciences | UniAcademia | 2022 - 2025

Key Areas: Molecular Biology Genetics Computational Biology Research Methodology Laboratory Management Scientific Publishing

Academic Excellence: GPA 3.7 | Thesis: Epigenetics Antiaging Health Software Leveraging Machine Learning & Deep Learning Algorithms

Bachelor of Science - Philosophy (Major) & Psychology (Minor) | Georgia State University | 2017 - 2020 (incomplete)

Key Areas: Cognitive Sciences Philosophy of Mind Psychology Human Behavior Research Methodology Academic Leadership

Academic Excellence: GPA 3.8 | Thesis: Differentiating Factual Belief, Imagination & Religious Credence - A Systematic Theory of Cognitive Attitudes

Additional Recognition: Columnist for "The Signal" (GSU's award-winning newspaper), Atlanta Campus Scholarship recipient, Dean's List, Honor Society member

View all recommendations on LinkedIn

I've been fortunate to work with exceptional professionals who have recognized my technical capabilities, problem-solving approach, and collaborative leadership style. These recommendations span my work in:

• AI/ML Engineering & Research
• Data Science & Analytics
• Project Leadership & Team Collaboration
• Academic Research & Scientific Methodology

This portfolio showcases end-to-end AI systems I've architected to solve real-world challenges. Each project demonstrates business impact, technical excellence, and production-ready implementation.

🏆 1st PLACE WINNER - Reply Enterprise Challenge @ FIAP NEXT 2025 🏆 An end-to-end, production-grade predictive maintenance platform I built from scratch (investing hundreds of hours) to win Reply's annual enterprise challenge. This system uses a 12-agent event-driven architecture (FastAPI, Redis) and 17 ML models (trained on 6 real-world datasets like NASA, AI4I, XJTU) to predict equipment failures before they happen.

• Business Value: Proven to reduce unplanned downtime by 40% and save R$ 100-500k per prevented failure.
• Performance: Validated at 103.8 RPS with 3ms P99 latency under load.
• Database: Achieved 37% faster dashboard queries using TimescaleDB continuous aggregates.
• Stack: Python • FastAPI • TimescaleDB • MLflow • Docker • AWS • Streamlit (NDA Expired - Repository open for architectural review)

Solo Development | AI-powered invoice processing automation

• Business Goal: To eliminate the slow, error-prone manual process of invoice handling for small to medium businesses.
• Solution & Impact: Built a full-stack system that automates the entire invoice processing pipeline. By mapping the user journey and applying RAG for intelligent error handling, the system reduced manual processing time by over 85%.
• Technologies: React.js • Next.js • TypeScript • FastAPI • LangChain • RAG • FAISS • Docker • AWS S3 • PostgreSQL

🏆 Award Winner - FIAP Global Solution 2025.1

• Business Goal: To create a predictive system to manage and mitigate large-scale national crises like natural disasters.
• Solution & Impact: I single-handedly architected and developed this award-winning multi-agent platform. Five autonomous "Guardian" agents for different threat domains, with a fully functional MVP for fire risk prediction using real-time IoT sensor data.
• Technologies: Agentic AI • Python • FastAPI • Docker • MicroPython • ESP32 • IoT • Apache Spark

Solo Development | Personalized anti-aging recommendation system

• Business Goal: To create a scalable HealthTech platform that provides personalized, data-driven health recommendations, moving beyond generic advice.
• Solution & Impact: Developing an AI platform focused on Explainable AI (SHAP) and secure deployment (JWT). The system translates complex epigenetic data (BioPython) into actionable health insights by analyzing genetic predispositions (SNPs) and lifestyle habits to generate personalized risk assessments.
• Technologies: PyTorch • Scikit-learn • BioPython • MLFlow • SHAP • Docker • FastAPI • React

End-to-End Architecture | Unified smart farming system integrating IoT, Cloud, and Hybrid AI

• Business Goal: To optimize agricultural ROI by minimizing water usage and crop loss through real-time telemetry and automated decision-making.
• Solution & Impact: A massive 6-module ecosystem combining Edge AI (YOLOv5) for pest detection and Cloud AI (GPT-4o) for insights. Features a custom Genetic Algorithm that solves the "knapsack problem" for crop allocation and a distributed ESP32 IoT network for predictive irrigation.
• Technologies: Python • AWS • IoT (ESP32) • YOLOv5 • Genetic Algorithms • OpenAI API • SQLAlchemy • Streamlit

Student Lead & Architect | Automated B3 Stock Analysis & Prediction System

• Business Goal: To automate the complex detection of Elliott Wave market patterns, creating a professional-grade technical analysis tool for the Brazilian Stock Exchange (B3).
• Solution & Impact: Led the research and development of a full-stack ML system processing real-time market data. Built a custom feature engineering engine (24 technical indicators) and an MLOps pipeline (MLflow + AWS S3) to train and version Random Forest/SVM models. The system classifies market movements into 4 strategic categories via a Streamlit UI.
• Technologies: Python • MLflow • AWS S3 • Docker • Scikit-learn • Streamlit • FastAPI • Technical Analysis

Lead Developer | High-performance bovine ancestry analysis pipeline for Embrapa

• Business Goal: To solve computational bottlenecks in genomic ancestry analysis and democratize access to complex tools for researchers.
• Solution & Impact: Architected a Nextflow automation pipeline that handles data conversion, Quality Control, and visualization. Introduced a parallelized Cross-Validation engine (reducing scan times drastically) and a Streamlit Web UI, allowing non-coders to run scientific-grade population structure analyses.
• Technologies: Nextflow • Python • Streamlit • R • Bioinformatics • Parallel Computing • Docker

As a Project Leader in the international SuperDataScience community, I led diverse teams of data scientists and ML engineers to deliver production-ready AI/ML platforms. I was responsible for aligning project priorities with stakeholders, defining KPIs, and managing deployment.

Leadership Experience: Project Lead for 2 projects | Project Member for 2 projects

Project Lead | Comprehensive diabetes risk assessment system using the CDC diabetes dataset

Led a diverse team of data scientists and ML engineers to deliver both beginner-friendly and advanced deep learning solutions.

Key Features: Built traditional ML models (Logistic Regression, Decision Trees) and advanced Feedforward Neural Networks with hyperparameter tuning. Includes model explainability tools and multiple deployment options.

Technologies: Python • Scikit-learn • Deep Learning • Streamlit • Model Explainability • Healthcare AI • Data Science

Live app: glucotrack.streamlit.app

Project Lead | End-to-end salary prediction platform analyzing the 2024 machine learning job market

Coordinated a team of data scientists and ML engineers to build comprehensive solutions across multiple skill levels.

Key Features: Analyzes global salary trends and job feature impacts on compensation. Features both traditional ML pipelines and advanced deep learning on tabular data with embeddings and explainability.

Technologies: Python • Scikit-learn • Deep Learning • Tabular Data • Streamlit • Job Market Analytics• Data Science

Project Member | End-to-end machine learning platform to predict Total Cost of Attendance for international higher education

Key Features: Achieved a 96.44% R² score with an XGBoost Regressor, deployed via both a Streamlit web app and a FastAPI service, all containerized with Docker and automated with CI/CD.

Technologies: Scikit-learn • XGBoost • MLflow • Streamlit • FastAPI • Docker • CI/CD• Data Science

Project Lead | Agentic AI system for automated institutional-grade financial research

Led the development of an autonomous multi-agent system that mimics a professional financial analyst team.

Key Features: Orchestrates 5 specialized agents (Researcher, Quant Analyst, Reporter) using Shared Vector Memory to scrape real-time news, calculate financial ratios, and synthesize findings into investment-grade reports. Implements "Advanced Track" architecture using CrewAI concepts.

Technologies: Python • CrewAI • OpenAI Agents • RAG • ChromaDB • Streamlit • Financial APIs

Project Member | Deep learning solution that classifies 14 different crop diseases across four species

Key Features: A Convolutional Neural Network (CNN) trained on my local machine, on over 13,000 images, using only modulerized python scripts (no notebooks), deployed via a user-friendly Streamlit interface for real-time predictions. Covers corn, potato, rice, and wheat diseases.

Technologies: Deep Learning • Computer Vision • CNN • TensorFlow • PyTorch • Streamlit• Locally Trained Neural Network

... and even more projects in my repositories, covering Data Science, Machine Learning, MLOps, LLMOps, IoT, AI engineering, bioinformatics, and more!

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