BELLA MENG
Senior Software Engineer | Product & cross-platform engineering
Product-minded Senior Software Engineer at Goodnotes with experience shipping consumer features end-to-end across web, iOS and desktop. Strong in React and TypeScript with Swift, Node.js and Python experience, and comfortable moving across product, platform and AI-enabled engineering problems. Currently part of Goodsystems, a highly AI-native team building shared platform capabilities and early-stage products.
EXPERIENCE
Senior Software Engineer
Goodsystems | AI-native product & platform team
- Build a shared canvas SDK used across multiple Goodnotes products, designing reusable APIs and platform capabilities that support distinct product experiences from a common foundation.
- Delivered Ondera.co, taking ambiguous requirements through rapid prototyping, technical spikes, architecture, implementation and iteration.
- Work AI-native: orchestrate multiple coding agents in parallel, strengthen agent harnesses and context/tooling, and use agents across prototyping, debugging and implementation to improve delivery speed and developer experience.
- Before moving to Goodsystems, launched the Goodnotes app on ChatGPT and built MCP-based agentic integrations connecting Goodnotes capabilities to AI assistants.
- Partner closely with product and design on technical and product trade-offs; mentor engineers and contribute to architecture, testing and code-quality practices.
Software Engineer
- Built and shipped cross-platform product features using React, TypeScript, Swift and Swift-WASM across web, iOS and desktop from a shared codebase serving millions of users.
- Owned features end-to-end from technical discovery and design through implementation, automated testing, rollout and iteration.
- Built maintainable, well-tested systems using TDD and improved developer experience through code review, tooling and documentation.
SELECTED PROJECTS
SnugBox AI-powered floor-plan furnishing tool
github.com/snugbox/snugbox- Won 1st place at the Granola AI x Google DeepMind hackathon with a product that generates furnishing layouts from uploaded floor plans and lets users refine them in an interactive editor.
- Built the React/TypeScript product in a monorepo, combining AI-generated suggestions with a custom isometric rendering experience and taking the idea to a working prototype under tight time constraints.
EDUCATION
M.Phil. in Data Science and Analytics
HKUST · Research focus: large-scale graph mining and data analysis. Coursework included Machine Learning and Knowledge Discovery in Databases.
B.Sc. in Computer Science and Mathematics
HKUST · First Class Honours; Dean's List.
SKILLS & INTERESTS
Languages
TypeScript, Python, Swift
Product & mobile
React, Node.js, Swift-WASM, iOS, cross-platform development
AI & developer experience
LLM integrations, agentic workflows, MCP, multi-agent orchestration & harnessing
Engineering practices
TDD, CI/CD, monorepo architecture, end-to-end ownership, technical discovery, code review, developer tooling, Git
Interests
Running & endurance training, strength training, boxing, Pilates