Samuel Edwin

Role: Senior front-end engineer and technical lead
Contributions: Led front-end architecture serving 860,000+ users, mentored development team.

Business challenge: Indonesian gov agencies needed a modern procurement platform to replace their legacy system, which required transparency, compliance, and complex eCommerce workflows for millions of transactions.

Technical approach: Built a Next.js app with SSR for SEO, state management for complex shopping cart synchronization, React Query for data fetching, and a coordinate-based PDF document signing system.

Key features: Multi-step procurement workflows, real-time WebSocket notifications, sophisticated search with URL persistence, PDF generation with signature placement, and file upload pipeline with virus scanning integration.

Business impact: Serves 860,000+ monthly active users across government agencies, processes millions in transparent transactions, prevents corruption through end-to-end audit trails, and replaces poorly performing legacy systems.

Technical proof points: Optimized performance for gov-scale traffic, implemented complex state management across procurement workflows, built reusable component architecture, and established front-end development standards.

Role: Senior front-end engineer and architect
Contributions: Designed and built a compliance management system for government vendor oversight.

Business challenge: Indonesian government agencies lacked a centralized system to track vendor violations and prevent non-compliant businesses from participating in procurement processes.

Technical approach: Built Next.js application with multi-step form architecture, server-side draft persistence, React Hook Form for form validation, and service-oriented design enabling cross-system blacklist queries.

Key features: Multi-page forms with conditional logic, server-side draft management, automated PDF generation, comprehensive audit trail system, real-time blacklist status API for procurement blocking across government systems.

Business impact: Enables government-wide vendor compliance tracking, prevents fraudulent businesses from procurement opportunities, provides forensic capabilities for investigations, ensures regulatory compliance across agencies.

Technical proof points: Complex form state management with server persistence, dynamic Excel export with lazy loading optimization, integration architecture for system-wide blacklist queries, comprehensive audit tracking for compliance.

Role: Technical co-founder and lead engineer.
Contributions: Led technical development from zero to paying customers, managed contractors.

Business challenge: Pharmaceutical companies lacked AI-powered tools for medical affairs teams to analyze insights, track performance, and generate executive reports. Manual processes cost directors significant time.

Technical approach: Built a full-stack platform with Next.js/React front end, tRPC API layer, PostgreSQL back end, integrated with multiple LLM providers for AI analysis and intelligent database search.

Key features: An intelligent AI chatbot with structured parameters, automated PDF/PPTX executive reporting, multi-LLM integration, and monthly trend intelligence processing of entire datasets to distill top discoveries with research citations.

Business impact: Live platform with paying enterprise pharmaceutical customers, eliminates hours of manual slide creation, and provides quantified ROI through data-driven medical strategy insights.

Technical proof points: End-to-end TypeScript validation, complex document generation with React-PDF, enterprise security with private IP databases, and cost-optimized AI integration for input-heavy workloads.

Role: Senior React Native engineer
Contributions: Built an AI-powered mobile healthcare app with on-device LLM integration in one month.

Business challenge: Memory-impaired users needed a voice-activated assistant for daily activity tracking and medication reminders, requiring an accessible mobile solution.

Technical approach: Built a React Native app with hybrid AI processing using an on-device Llama model for free users, a cloud LLM for premium users, and integrated iOS speech recognition for voice interaction and healthcare data management.

Key features: On-device 1GB Llama model processing, hybrid local/cloud architecture, real-time voice-to-AI pipeline, state machine WebSocket management, healthcare-compliant data persistence with wipe functionality.

Business impact: A live iOS app serving memory-impaired users demonstrates cutting-edge on-device AI integration in a healthcare context and validates rapid mobile development capabilities.

Technical proof points: advanced Jotai state management for audio components, optimized 16,000 context window handling, WebSocket architecture bypassing API limitations, and healthcare privacy compliance.

Role: Senior React Native engineer and architect
Contributions: Rescued a delayed project, rebuilt codebase architecture, and delivered production app to 5000+ users.

Business challenge: An education organization needed a reliable mobile communication platform for its distributed business network after its WebView-based app proved clunky and unreliable.

Technical approach: Built a React Native chat application with GetStream SDK integration, custom native modules for iOS/Android, advanced gesture handling for voice recording, and cross-platform share extensions using Swift and Kotlin.

Key features: Custom voice recording with gesture controls, dynamic theming with real-time chat customization, advanced attachment system, push notification architecture with deep linking integration.

Business impact: Delivered a stable production app serving 5,000+ business owners, eliminated 90% of critical bugs, and established an ongoing client maintenance relationship demonstrating sustained value.

Technical proof points: 99% crash-free rate across platforms, eliminated React anti-patterns with modern TypeScript/React Query architecture, integrated complex SDKs with custom modifications, and maintained App Store compliance.

ROLE
React Native infrastructure lead

CONTRIBUTION
Pioneered React Native brownfield integration as an early adopter (2017).

TECHNICAL APPROACH
• Built a comprehensive infra API for brownfield integration.
• Solved complex React Native communication using callback-based architecture (pre-async/await era).
• Implemented advanced Redux state management for multi-screen workflows, including Uber booking integration with extensive state transitions.

KEY FEATURES
• Cross-platform brownfield APIs covering networking, authentication, navigation, deep linking, and push notifications.
• Complex Redux patterns for multi-screen applications, Facebook-style feed implementation, advanced state bridging between native iOS and React Native contexts with seamless navigation coordination.

BUSINESS IMPACT
• Delivered complex Ride Booking integration in a 2-month timeline.
• Grew React Native adoption from experimental feature to multiple production implementations, enabling web developers to build mobile features using React paradigms.

TECHNICAL PROOF POINTS
Early brownfield specialist (2017), complex native-React Native communication expertise, advanced Redux patterns, pre-async/await callback management, cross-platform API architecture.

Role: Senior iOS Engineer
Contributions: Completed iOS application from concept to App Store publication in a 2-month timeline, implemented AI integration and subscription system.

Business challenge: Spanish language learners needed hands-free conversational practice without text-based barriers. Existing apps required manual interactions that interrupted natural conversation flow.

Technical approach: Built a native iOS application with hybrid AI processing, combining Speech Recognition API for silence detection with GPT back-end integration. Implemented streaming communication and subscription management.

Key features: Hands-free conversational AI pipeline with silence detection, tiered subscription system with differentiated AI personalities, and seamless voice-to-text-to-speech processing.

Business impact: Successfully published an iOS app with a production-ready subscription platform, eliminated interaction barriers for voice-first language learning, and achieved App Store approval.

Technical proof points: AVFoundation audio session management with automatic cutoff detection, streaming integration for AI responses, webhook coordination with receipt validation, and conversation context management.

I led this project on the technical side, which involved improving the UI and UX of Tokopedia's existing home screen.

You can see the complexity of the feature in the video:
• Lots of different widgets are displayed on one screen.
• A sticky tab bar (0:11 in the video) that needed special care to implement.
• Pinterest-like layout at the bottom of the list.
• Needs to be smooth on iPhone 5, the oldest iPhone we support.

This was almost impossible to implement, especially the sticky tab bar. Nobody knew how to implement this at that time. I managed to find an elegant implementation by reverse engineering Instagram, which used the same UI pattern.

The previous iteration had many widgets, and the code was a mess to maintain. This iteration has many more widgets, but I managed to find a code structure that makes these widgets easy to maintain. Maintaining this feature is fun now, unlike before.

To make it smooth on iPhone 5, I learned new tricks from the iOS community to optimize UI performance. Scrolling on iPhone 5 now feels butter smooth. I achieved the Pinterest-like layout by applying my extensive knowledge of the iOS UI system.

Tokopedia has lots of UI designers working on multiple products. They don't frequently communicate, resulting in inconsistent UI behavior. This is a huge waste of time because engineers must repeatedly build the same UI components.

The engineering team and the UI design team solved this problem by creating a reusable component library.

Here are my contributions to this project:
• Talking to UI designers whenever something was impossible to implement and offering alternative solutions that work just as well.
• Brainstorming with engineers on how to implement tricky components.
• Building some of the UI components.
• Reviewing the components' API to make them easy to use.

This resulted in a huge productivity boost both for the engineers and the UI designers. Engineers didn't have to waste time rebuilding the same components anymore, and UI designers didn't have to reinvent new ones. They can now simply pick a UI element from the catalog and plug it into Figma.

I led this rewrite project with one team member. This rewrite was necessary because of a few reasons:
• Thousands of lines in one file, very hard to understand.
• Crashes frequently.
• Lots of bugs.
• Slow performance.

Here's what I did to solve these problems:
• Developed a coding pattern that makes it easy to maintain a large number of different widgets.
• Used Swift's language features to make crashes almost impossible to happen.
• Reduced the amount of code written significantly by adopting a framework called IGListKit.
• Adopted a new UI framework to make the performance smooth.

The Tokopedia app contains dozens of different products. The app supports eCommerce activities, paying monthly bills, booking flights, social commerce, and much more. This means the codebase is huge, which takes a lot of time to build. It can take 30 minutes to build a project, wasting a lot of engineers' time.

I led this project along with two engineers with one main goal—to improve the engineers' productivity by improving build speed.

I did two things here; the first one is splitting the code into multiple modules, ensuring that rebuilds only happen for the code that we change. To make this happen, I learned the inner workings of the Xcode build system to learn why rebuilds happen. The second one is adopting Bazel as our build system. Using Bazel's cache, we can shave off more time to build our app. We now only need to spend around two minutes for our app to build successfully.

At Tokopedia, we use a lot of back-end services in the app. It is often hard to know when something went wrong with the back-end side.

I contributed to this project by talking to engineers and their managers to define such problems. I prioritized solving the issues in the order of their occurrence rate.

Here are some issues we often encounter:
• Images often don't load under specific internet providers.
• Some features suddenly don't work because of a back-end deployment that went wrong.
• Wrong deep link URLs stop the users from navigating to a particular screen.

We then used New Relic to log all the problems described above. We built dashboards and alerts to be notified immediately when something went wrong, so the troubleshooting time goes way faster. This makes our engineers feel safe because whatever problems that show up, they have the tools to solve them.

A tvOS app that provides entertainment through streaming TV shows similar to Netflix.
I translate the design from Figma into a usable app used by end-users.

One particularly challenging part of the project is managing the focus for remote controls, which I learned a lot from this project.

Technologies used:
• SwiftUI
• Combine
• Composable Architecture (Redux)

A Next.js app that I built to demonstrate my skill in building a full-stack React app. It has several functionalities: create/edit a new shop, add/edit products, and manage catalogs for the shop.

To get the best performance, every page is rendered with server-side rendering to reduce API request delays. The security aspect was also taken care of. Only the shop's owner can edit the shop's information and products. AI generates the shop's names, descriptions, and images entirely.

A custom website redesign for FCamara UK.

My main task was to build the website pages using designs in Figma as a reference.

The website was built using Next.js and Tailwind CSS. It also has a Cloudflare CAPTCHA on the contact page to prevent bots from filling out the contact form, which reduces the spam rate by 95%. This website has responsive designs accommodated for phones, iPads, and laptop screens. I improvised the iPad design by finding inspiration online and applying what I learned to build the layout.

The designer didn't have the design for the tablet layout.

The website is hosted in Azure. I built it using GitHub Actions and uploaded the build to Azure.

A set of reusable React components based on this Figma (Figma.com/community/file/1405573618937136138/gumroad-design-system-community-beta).

Implemented with React, Tailwind CSS, TypeScript, and StoryBook.

The components implemented are:
• Alert
• Button
• Checkbox
• LikeButton
• Modal
• Pill
• Radio
• Toggle
• Tooltip

A responsive website implemented with Next.js, React, and TailwindCSS.

This is a website that clones some of the pages from gumroad.com. The goal of this project is to showcase my responsive web development capabilities. This website supports mobile, tablet, and desktop layouts. Dark mode is also supported on this website.

A nearly production-ready GraphQL server incorporating industry best practices. Written in TypeScript, Apollo GraphQL, and SQLite.

• Well-designed schema with reusable objects.
• Standard authorization: Users can only modify products for their own shop, etc.
• Field-level authorization: Only admins and shop owners can see the shop's address, and only admins and the user can see the user's date of birth.
• Malicious query protection: Queries beyond a certain depth are rejected.
• Data loader pattern to prevent N+1 query problem.
• Relay compliant pagination.
• Input limit validation.
• Robust error handling.
• 100% type safety with TypeScript and GraphQL Code Generator.

An initiative in govtech procurement to optimize costs through downsizing CloudSQL usage.

I did several things to make this happen:
• Optimized slow queries to reduce CPU usage by adding indexes and rewriting queries.
• Dropped unused data to save disk space.
• Offloaded transactional data over a year to Google Cloud Storage for archival purposes.

Once the above actions were done, I performed a system migration by:
• Running a database management system (DMS) to create a new CloudSQL instance with smaller compute, memory, and disk size.
• Turned on maintenance mode on Cloudflare to stop incoming traffic.
• Migrated all apps to connect to the new CloudSQL instance.
• Deleted the old instance.

RESULT
• Disk usage down from 2TB to 130GB
• CPU usage down from 16 vCPU to 4 vCPU
• Memory usage down from 64GB to 16GB
• Total CloudSQL cost down by 90%

The audit trail is required to solve problems such as user requests, disputes, and complaints. The goal is to provide supporting relevant data whenever such things happen.

This system captures some activities:
• Request logs with sensitive information stripped
• Auth-related activities such as login, logout, two-factor authentication (2FA) changes, and other information such as email and phone number
• Changes to tables that have important information

HTTP requests are logged by the framework's middleware, sensitive data is filtered out, and pushed to PubSub, which forwards the request to BigQuery.

Changes to the SQL tables are captured with Debezium. A dedicated microservice processes the CDC payload, which pushes the final payload to the PubSub BigQuery pipeline.

RESULT
The average problem-solving time goes down from three hours to one hour.

The Indonesian government wants to move this on-prem system to the cloud for these reasons:
• Cost efficiency
• Autoscale workloads on occasional high traffic
• Better uptime through a cloud high-availability setup
• Easier deployments
• Automated database backup

My involvement is in rewriting the applications, making them stateless so they can run on the cloud with replicas:
• Removing file system usage.
• Storing user sessions on Redis.
• Deploying the microservices to Kubernetes.
• Migrating database to GCP CloudSQL.
• Improving stability by solving deployment issues and application bugs.

Designed a production-ready video processing pipeline demonstrating AWS cloud architecture expertise, converting uploaded videos into HLS playlists with multiple resolutions for optimal streaming.

Technical approach: Built an event-driven serverless architecture using AWS Media Convert over Lambda ffmpeg for superior performance and cost efficiency. Implemented a dual SQS queue system with CloudWatch Events for reliable processing.

Key features: HLS generation with 4-tier adaptive resolution, portrait/landscape intelligence, thumbnail generation, Dead Letter Queue error handling, and automatic cleanup.

Contributions: Architected a complete solution across 8+ AWS services (S3, SQS, Lambda, MediaConvert, DynamoDB). Developed sophisticated IAM security with least privilege principles. Built Infrastructure as Code using Terraform.

Business impact: Demonstrates AWS expertise with event-driven patterns, cost-optimized decisions, and production-grade reliability for scalable video processing.

Role: Solo Technical Consultant | UI Designer | Full-stack Architect

Business challenge: An Indonesian coal mining company operated through Excel spreadsheets and manual paperwork, creating inefficiencies and compliance risks across multi-pit operations.

Technical approach: Built a TypeScript monorepo (Hono, React, and PostgreSQL) with role-based mobile and desktop workflows, AI document processing, and regulatory compliance automation.

Key features: Multi-pit operations management, real-time truck monitoring via QR and GPS, AI-powered laboratory processing, financial workflows, regulatory compliance engine, multi-role access control.

Contributions: Led the project lifecycle from requirements gathering to deployment. Designed database schema modeling geological data and financial workflows. Architected a responsive mobile and desktop solution. Implemented AI document processing with verification workflows. Developed a regulatory compliance calculator. Managed client relationships through scope control and iterative validation.

Business impact: ERP replacing Excel workflows for 10+ users. Client validated commercial potential for broader mining distribution. Automated compliance and eliminated paper-to-analysis delays.