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Ellie Le
July 2, 2025
12 min read
Career
Development
QA
Learning
Full-Stack
AI

My Journey from QA Engineer to Full-Stack Developer

Coming from a business background, I spent four years studying Business Administration and working on several marketing research projects. That time taught me how to identify and frame real-world business problems — but more importantly, it sparked a question I couldn't stop thinking about: How can I not just understand a problem, but actually solve it better?

That curiosity is what started my journey into tech.

The Beginning: From Business to Code

I knew I didn't have a strong technical background at first, but I genuinely enjoyed the process of learning — even if it meant starting from scratch. I began teaching myself Python, SQL, and analytics from the ground up.

At the time, I was working as a QA engineer, and I started applying what I was learning to automate test cases and analyze data more meaningfully. Eventually, I found myself staying up late just to keep exploring.

That's when I made a big decision: I enrolled in a Bachelor of Computer Science while working full time. It wasn't easy, but it made a huge difference in how I worked and thought. It gave me a new lens for solving problems.

Deepening My Technical Skills

Later, I decided to go deeper into AI and data by starting a Master of Information Technology. The combination of practical work experience and academic learning created a powerful foundation for tackling complex technical challenges.

Key Skills I Developed:

Programming Languages:

  • Python for data analysis and backend development
  • JavaScript/TypeScript for full-stack web development
  • C/C++ for system-level programming
  • SQL for database management

Frameworks & Technologies:

  • React and Next.js for frontend development
  • Express.js and Flask for backend APIs
  • Socket.IO for real-time applications
  • Docker for containerization

Data & AI:

  • Machine learning with scikit-learn
  • Statistical analysis with NumPy and pandas
  • Database design and optimization
  • API integration and development

Real-World Application: AI-Powered Business Intelligence

One of the most exciting projects I've worked on recently is an AI-powered business intelligence platform I'm co-developing with five other students at UNSW for a private client.

The Vision

It's designed to help users discover and implement automation workflows through natural language input, semantic search, and personalized progress tracking.

My Role

My focus is on building the semantic search engine and implementing personalized analytics — tracking user progress, benchmarking performance, and delivering tailored insights.

How It Works

The platform starts with a user typing in something like "I spend 3 hours a day qualifying leads", and returns actionable, ranked solutions with ROI estimates.

Technical Implementation

Semantic Search Engine:

  • Built using SentenceTransformers for embedding generation
  • FAISS vector indexing for efficient similarity search
  • Custom ranking algorithms based on user context and business impact

Personalized Analytics:

  • User behavior tracking and pattern recognition
  • Performance benchmarking against industry standards
  • Tailored recommendations based on usage patterns
  • ROI calculation and progress visualization

Lessons from the QA-to-Development Transition

1. Testing Mindset is a Superpower

My QA background gave me a unique advantage in development. I naturally think about edge cases, error handling, and user experience from a quality perspective. This has made me a better developer who writes more robust, reliable code.

2. Understanding the Full Software Lifecycle

Having worked in QA, I understand the importance of:

  • Comprehensive testing strategies
  • Documentation and maintainability
  • Cross-functional collaboration
  • User-centric design thinking

3. Problem-Solving from Multiple Angles

My business background taught me to understand problems from a user and business perspective, while my technical skills allow me to implement solutions. This combination is powerful for building products that actually solve real problems.

Key Projects That Shaped My Journey

Real-Time Chat Application

Built a full-stack chat application with React, TypeScript, Socket.IO, and MongoDB. This project taught me about:

  • Real-time architecture and WebSocket management
  • File handling and storage systems
  • Scalable backend design
  • User experience in real-time applications

Machine Learning Pipeline Development

Developed end-to-end ML pipelines using scikit-learn with custom transformers and modular architecture. Key learnings:

  • Feature engineering and selection techniques
  • Model evaluation and comparison
  • Production-ready ML system design
  • Performance optimization for large datasets

Chalkboard Education Platform

Built a comprehensive education platform with Flask, Auth0, and Google Cloud Platform:

  • Role-based access control systems
  • RESTful API design and implementation
  • Cloud storage integration
  • Scalable authentication systems

The Continuous Learning Mindset

What I've learned is that the transition from QA to full-stack development isn't just about learning new technologies — it's about developing a continuous learning mindset.

Current Focus Areas:

  • AI and machine learning applications
  • Scalable system architecture and design
  • Data engineering and analytics platforms
  • Modern web development frameworks and best practices

Looking Forward

The journey from QA engineer to full-stack developer has been challenging but incredibly rewarding. Every day brings new problems to solve and new technologies to explore.

Currently, I'm excited about:

  • AI and Machine Learning: Building intelligent systems that can solve complex business problems
  • Data Engineering: Creating pipelines for processing and analyzing large datasets
  • Full-Stack Development: Building end-to-end applications that provide real value to users

The combination of business understanding, quality assurance mindset, and technical development skills has created a unique perspective that I bring to every project.

Conclusion

The transition from QA to full-stack development isn't just a career change — it's a mindset shift toward continuous learning and problem-solving. My business background taught me to understand problems, my QA experience taught me to think critically about solutions, and my development skills allow me to build those solutions.

If you're considering a similar transition, remember that your existing experience is valuable. The key is to build on what you know while continuously expanding your technical skills.

The journey continues, and I'm excited to see where it leads next.


Want to connect or learn more about my projects? Feel free to reach out on LinkedIn or check out my work on GitHub.