Hi, my name is
Zaw Lin Naing.
I build things for the web.
Results-driven full-stack software engineer with 7+ years of experience in the JavaScript ecosystem. I build reliable, scalable, and maintainable systems, and effectively leverage AI coding agents to boost productivity and code quality.
01.Skills & Technologies
02.Experience
Jul 2024 — PRESENT
Senior Software Engineer · Sertis
CONTRIBUTIONS
- Led the adoption of AI Agent Skills to embed structured engineering expertise into AI agents (e.g., Claude Code, Copilot), aligning agent behavior with internal standards for estimation, feature discovery, and code review, and built the necessary CLI tooling to be used by AI agents.
- Implemented a production-grade PDF platform with annotation, dual-document comparison, intelligent search, and AI-powered detection of tables and document assets, with strong focus on performance, scalability, and clean architecture.
- Led technical research and architectural decisions for PDF viewer integration, defining implementation standards and serving as the domain authority for the team.
- Designed and delivered a large-scale LLM-based conversational AI platform by integrating in-house AI services, ensuring robustness, maintainability, and production readiness for enterprise adoption.
- Defined and enforced frontend engineering standards, code review practices, and architectural guidelines to raise overall code quality and long-term maintainability.
CHALLENGES & IMPACT
- Delivered complex features under frequently changing requirements while maintaining high engineering standards, strong test coverage, and system reliability.
- Re-architected a resource-intensive monolithic system into modular, purpose-driven components with clear separation of concerns, achieving 80% performance improvement and significantly better resource efficiency.
- Proactively identified technical risks, drove refactoring initiatives, and balanced delivery speed with sustainable design to prevent long-term technical debt.
- Mentored engineers and promoted knowledge sharing to ensure consistent application of modern engineering practices across the team.
TypescriptPythonNode.jsReact.JSNext.jsAngularSvelteNestJSGolangPostgreSQLRedisDockerKubernetesTerraformAmazon Web ServicesMicrosoft AzureGoogle Cloud Platform
Sep 2023 — Jul 2024
Full-stack Engineer · Oozou
CONTRIBUTIONS
- Core developer of beta.slimwiki.com, implementing rich-text editor with ability to format texts, insert images, videos, links and create interactive tables.
- Developed editor version history, wiki search and super-admin dashboard features.
- Improved editing experience by implementing a real-time collaboration feature with Conflict-Free Replicated Date Type(CRDT).
CHALLENGES & IMPACT
- Research and benchmarked various WYSIWYG editor libraries that offer stability, maintainability and extensibility.
- Setup client codebase structure to streamline feature development for other developers, enabling seamless implementation of optimistic updates, data caching, and cache validation by integrating state management with data fetching.
- Reduced API calls and page load performance for the new editor; providing better user experience.
TypescriptNext.jsReact.JSTailwind CSSNode.jsPostgreSQLRedisDockerAmazon Web ServicesReal-time WebsocketYjs
Feb 2023 — Aug 2023
Software Engineer - Backend · Brikl
CONTRIBUTIONS
- Mentored a fellow engineer, providing guidance and better solution suggestions.
- Improved integration testing flow enabling developers to seed and cleanup test data with ease. Reducing lines of code to write tests by half.
- Implemented scalable bulk upload products feature that can import multiple data points for products using serverless framework.
- Enhanced pricing feature adding price markups, tiered pricing and cost configurations; allowing merchants to update price and automatically propagated to all micro-stores.
- Enabled data collection for merchants from their customers in checkout flow using custom data fields.
CHALLENGES & IMPACT
- Solved n + 1 issues on GraphQL queries, reducing latency, database calls and inter-service communication.
- Optimized batch operations with complex business logic to be executed under constant time.
GraphQLTypescriptNode.jsPostgreSQLPrisma ORMRedisAmazon Web ServicesServerless
Jan 2022 — Feb 2023
Full Stack Engineer · Taskworld
CONTRIBUTIONS
- Optimized Kanban board performance and memory usage (from linear space complexity to constant space complexity), enabling smooth user interaction and experience even when there are thousands of items inside the board.
- Extracted and deployed a micro service from legacy monolith codebase, allowing easier maintenance and faster development speed.
- Developed project templates, starter templates, and pinned task features in a timely manner.
CHALLENGES & IMPACT
- Developed and modified complex features on the platform with little or no regression.
- Navigated through complex and legacy codebase to identify performance bottlenecks and implemented optimization solutions.
TypescriptNode.jsMongoDBElasticsearchReact.JSReduxRedisReal-time WebsocketDockerKubernetes
Jan 2020 — Aug 2021
Software Engineer · Expa.AI
CONTRIBUTIONS
- Revamped and extended a social commerce platform (using Node.js and React.js) which integrates with Facebook API and enables SME users to sell products via Facebook Messenger.
- Developed live chat plugin (using React.js) that can be used on websites even without React.js.
- Built an analytics solution for the social commerce platform (with Node.js and open-source data visualization library) which enables users to gain insight into their storefronts.
- Coded an AI-driven feature that delivers automated responses, on behalf of businesses, to customers’ queries, and enables businesses to improve AI models iteratively using real-world conversations over time.
- Worked on the AI management server which allows businesses to deploy their own models instantly on the dashboard, and automatically scales those models depending on the usage.
CHALLENGES
- Ensured product quality through rapid iterations of the development process
- Implemented Event-Driven Architecture for storing user activity logs.
- Solved N+1 problems and implemented IAM on GraphQL server.
Node.jsGraphQLMongoDBPostgreSQLReact.JSRedisReduxDockerKubernetes
May 2019 — Nov 2019
Web Developer · Mounts Digital
CONTRIBUTIONS
- Developed backend system for ERP solutions using Laravel and MySQL.
- Built a location tracking feature for the delivery management platform by integrating with Firebase and Google Map‘s API.
- Developed video chatting feature by integrating with open-source library and using Javascript.
CHALLENGES
- Designing DB schema for ERP systems that fit business needs.
- Ensuring consistency and robustness for cascading writes across multiple tables.
- Writing and debugging complex and performant queries that span across multiple tables.
- Designing REST APIs for multiple platforms including web, android and ios.
LaravelMySQLJQueryRedisFirebaseGoogle Map API
Dec 2018 — Feb 2019
Intern · Nexlabs
CONTRIBUTIONS
- Reviewed code for a project to learn about code architecture, coding styles from senior developers.
- Collaborated with senior developers in debugging process and removing dead code.
- Developed a blog app (with Nuxt.js and Laravel) to put my learned skills into use.
LaravelMySQLVue.jsNuxt.js
03.Projects
AI-review CLI is an open-source command-line tool that lets AI coding agents (Claude Code, Cursor, GitHub Copilot, etc.) perform automated code reviews on GitLab Merge Requests. It handles the integration work — authenticating with GitLab, fetching and normalizing diffs, annotating line numbers, and posting structured inline comments to provide context for AI agents to review. Developers run
ai-review get-context <MR_URL> to pull a structured JSON snapshot of the MR, feed it to their AI agent of choice, then use ai-review post-comments to publish the results back to GitLab. Built in TypeScript on Node.js, it ships as both an npm package and pre-built binaries for macOS, Linux, and Windows, with a provider abstraction layer designed to support GitHub in a future release.TypescriptNode.js
Zen Mode Extension is a Chrome browser extension that I developed to optimize productivity and minimize distractions. It empowers users to regain control over their online experience by blocking access to up to 5000 domains. As a testament to its versatility, this extension also boasts a search functionality, enabling users to effortlessly search for and unblock specific websites that may be temporarily restricted. By integrating comprehensive website blocking features with a user-friendly search function, Zen Mode Extension offers an efficient solution for enhancing productivity and maintaining focus during web browsing.
TypescriptReact.JSViteChrome Web Extension
Other Noteworthy Projects
Zen Player
Zen Player is a side project, I am currently working on. It is a video player focuses mainly on preventing users from spending more time than it should be on YouTube videos. Due to YouTube recommendation, we often tend to watch more videos than we originally came for. Thus, lots of time wasted on watching videos that are not related to our search intention. The main features I am currently working on includes ability to search videos by name or url on YouTube, provide analytics on watch time, allow maximum watch timer for each day, allow creating queues and looping of videos. It will be available on both web and android.
Flutter
Portfolio Website (This One)
This portfolio website is built using both Gatsby.js and Tailwind CSS. I also enabled DevOps using GitHub Actions which deploy the website to GitHub Page every time I push code changes to a specified branch. I built this website as an opportunity to learn two technologies I have been wanting to learn, Gatsby.js and DevOps.
Gatsby.jsTailwind CSSGitHub Page
Tensorflow Implementation of CAN
I built this project as my graduation thesis and also a way to learn in-depth about Tensorflow. I forked from the original repo and worked on Tensorflow implementation of Creative Adversarial Network (CAN) model which generates creative art works by training upon art styles dataset. My main contribution for the project includes;
- Up-scaled Generator model output image by 2 times, including its neural network Parameters. (from 256x256 to 512x512)
- Transformed the code structure to a single file that can be trained on Google Colaboratory.
- Created trained checkpoint files for both original resolution model (256x256) and enhanced resolution (512x512) model.
PythonTensorflow
04. What's Next?
Let's Work Together
I'm currently open to new opportunities. Whether you have a project in mind, a question, or just want to connect — my inbox is always open.
Say Hello