Daniel – Python, Typescript, Node.js

This project focused on improving the onboarding experience for delivery drivers by transitioning from a synchronous, app-dependent process to an asynchronous, event-driven workflow. Previously, the onboarding flow required continuous engagement within the app, which caused significant drop-offs and reduced completion rates. The new architecture allowed applicants to complete onboarding tasks at their own pace, leading to a smoother experience and a measurable increase in successful onboarding. The migration involved a complete redesign of the workflow, ensuring scalability, improved reliability, and better user engagement.

• Oversaw the restructuring and modernization of the onboarding pipeline by designing and implementing robust back-end and front-end architecture using Kotlin, gRPC, and event-driven microservices to enhance scalability and responsiveness;
• Led the migration of synchronous onboarding processes into asynchronous workflows, significantly improving user experience and reducing dropout rates;
• Integrated critical compliance services such as Stripe and Checkr, enhancing data consistency and enabling asynchronous compliance checks that contributed to higher onboarding conversion rates;
• Decoupled compliance logic from the onboarding platform, consolidating checks under a centralized Trust domain and building scalable workflows adaptable to country-specific requirements;
• Developed comprehensive state management systems with robust error handling and retry mechanisms to handle complex compliance scenarios;
• Implemented thorough unit, integration, and end-to-end (e2e) testing, improving system reliability and reducing regressions;
• Coordinated and mentored a cross-functional team across multiple business units, fostering strong collaboration and high productivity;
• Swiftly resolved critical application issues, maintaining high service availability and ensuring quality throughout the project lifecycle.

This project focused on migrating ownership of a critical Trust & Safety domain from a seasoned US-based team to a newly formed engineering team in Brazil. The goal was to ensure continuity, system stability, and full onboarding of the new team into a complex and sensitive area of the platform. The transition involved deep domain knowledge transfer, replication of essential workflows, and rebuilding operational reliability with a smaller, less experienced team. Through system analysis, documentation, and collaborative sessions, the team successfully assumed full ownership without disrupting operations, demonstrating the strength and scalability of the migration strategy.

• Led the documentation and knowledge transfer process for the Trust & Safety domain;
• Successfully transitioned a complex engineering domain from a 20-member US team to a newly formed 5-member team in Brazil;
• Facilitated hands-on training and pair programming sessions to accelerate knowledge acquisition;
• Established detailed documentation and standard operating procedures;
• Ensured uninterrupted service and operations throughout the transition;
• Identified and resolved domain-specific technical issues during the migration;
• Developed comprehensive test plans and executed rigorous testing protocols;
• Enhanced system performance and reliability post-transition.

This project focused on automating the processing of large, complex purchase request files submitted by industrial clients through their unique ERP systems. Initially handled manually by an operations team, the process was time-consuming and error-prone. To address this, a web platform was developed using Next.js for the frontend and FastAPI/NestJS for the backend, enabling automated product identification and request handling. After multiple iterations and feedback cycles, the solution was refined into a lightweight Excel Add-in that seamlessly integrates into client workflows. Several custom machine learning models—including classification, two-tower architectures, and NLP-based solutions—were deployed to interpret and categorize diverse datasets. Later, generative AI capabilities were integrated using ChatGPT to further improve accuracy and response time.

• Led a cross-functional team of 15 software and AI engineers, driving end-to-end project execution and maintaining high technical standards;
• Architected and implemented scalable front-end and back-end systems using Next.js, FastAPI, and NestJS;
• Built and fine-tuned machine learning models, including classification, two-tower, and NLP-based solutions for automated product identification;
• Delivered a user-friendly Excel Add-in to improve customer integration and streamline workflows;
• Integrated generative AI (ChatGPT) to boost product-matching accuracy and reduce response times;
• Established and maintained a comprehensive testing strategy covering unit, integration, and end-to-end testing to ensure system reliability and performance.

The project involved developing an OKR management platform from scratch, starting with an MVP built using Next.js, NestJS, TypeScript, and React. After gaining early traction and market validation, the platform expanded with a growing team, incorporating feedback and refining features. The project secured pre-seed and seed funding, enabling further scaling and improvements. The platform became a competitive solution in the OKR management space, offering a user-friendly and adaptable tool for team alignment around measurable goals.

• Created the front-end and back-end architecture from scratch using NextJS, NestJS, React, and TypeScript;
• Designed and implemented advanced real-time analytics and notification systems;
• Built robust multi-tenancy database architecture to support scalable growth;
• Led strategic product discussions, aligning technical decisions with business goals;
• Mentored and expanded the product team, growing it to around 10 members, emphasizing professional development and collaboration, while simultaneously overcoming technical challenges associated with scaling our MVP into a stable and feature-rich application;
• Successfully secured pre-seed and seed funding rounds to accelerate product development;
• Rapidly developed an MVP in under one month, quickly capturing initial customers and validating product-market fit;
• Oversaw the implementation of key advanced features, including real-time analytics, social networking components, robust notification systems, and a sophisticated multi-tenancy database architecture.

The project focused on enhancing infrastructure and developer experience at a growing tech company. Initially, the focus was on developing communication microservices using Python, TypeScript, and Serverless technologies, scaling a notification system to handle millions of daily notifications, and integrating machine learning for dynamic property pricing. It expanded to include creating a Kubernetes-based serverless infrastructure using Kubeless, improving deployment efficiency. It also involved implementing real-time monitoring with Prometheus and Grafana to ensure system reliability. The project's success was recognized with a hackathon win.

• Built a Kubernetes-based on-premise serverless infrastructure using Kubeless from the ground up;
• Automated and simplified serverless function deployments across QuintoAndar, significantly improving developer productivity;
• Managed and resolved critical infrastructure issues, providing on-call support and ensuring high availability;
• Implemented comprehensive monitoring solutions using Prometheus, Grafana, and automated alerts via Statuspage;
• Contributed significantly to Kubeless, developing features, improving stability, and engaging actively with the open-source community;
• Developed and refactored microservices using Python, TypeScript, React, Redux, Serverless, DDD, and TDD methodologies;
• Redesigned the notification system to handle up to a million notifications daily, greatly enhancing user engagement;
• Implemented a smart-pricing feature utilizing machine learning to dynamically adjust property prices, optimizing market competitiveness;
• Mentored and provided technical leadership to junior engineers, fostering professional growth within the team.