Building reliable mobile applications, scalable backend services, and better engineering workflows.
I'm a software engineer with 10 years of experience building and maintaining production web applications, mobile products, and backend services.
My work sits at the intersection of mobile engineering, backend systems, and developer productivity. I enjoy taking features from business requirements to production—from application architecture and API design to database consistency, testing, observability, and releases.
I'm also an AI-assisted engineer, using tools such as Cursor, GitHub Copilot, and LLMs to accelerate development while maintaining control over architecture, code quality, security, and business logic.
- 📱 Mobile: React Native, TypeScript, Expo, native integrations
- ⚙️ Backend: Node.js, REST APIs, authentication, data modeling
- 🏗️ Architecture: Modular systems, maintainability, scalable application design
- ☁️ Infrastructure: AWS, GCP, CI/CD, monitoring, production debugging
- 🤖 AI-assisted engineering: Context engineering, reusable agent instructions, AI-assisted testing and code review
- 🚚 Domain experience: Logistics, last-mile delivery, fleet tracking, and enterprise workflows
Building reliable mobile applications that work under real-world constraints.
- React Native applications for Android and iOS
- Navigation, state management, permissions, and native SDK integration
- Background location, delivery workflows, and mobile lifecycle management
- Performance optimization, debugging, and production releases
Designing backend functionality that supports real business operations.
- REST API design and service integration
- Database modeling and transactional consistency
- Authentication, authorization, and multi-tenant systems
- Logging, observability, and production issue investigation
Using AI as an engineering tool—not a substitute for technical judgment.
- Structured project context and architecture documentation
- Reusable rules, skills, and agent instructions
- AI-assisted implementation, debugging, refactoring, and testing
- Human review of generated code against requirements and business rules
Developer productivity and code quality
Applying structured AI workflows to complex engineering tasks.
- Organize project context, architectural decisions, and implementation constraints.
- Use coding assistants to explore unfamiliar codebases and accelerate implementation.
- Generate and review tests, documentation, and debugging hypotheses.
- Validate changes against requirements instead of blindly accepting generated output.
Mobile: React Native, Expo, Android, native integrations
Frontend: React, Next.js, TypeScript
Backend: Node.js, REST APIs, Hono
Data: PostgreSQL, MySQL, SQL Server, Firebase
Cloud & Delivery: AWS, GCP, Docker, CI/CD, observability
AI tooling: Cursor, GitHub Copilot, LLM-assisted development
I care about the engineering practices that make software sustainable:
- Clear separation of concerns and modular architecture
- Explicit business rules and predictable state management
- Reliable testing and meaningful observability
- Secure APIs and data access
- Documentation that helps engineers and AI tools understand a codebase
- Faster delivery without sacrificing maintainability
I'm also expanding my knowledge of Kotlin, Android architecture, and data/AI engineering to broaden my ability to build across platforms and systems.
Building reliable software. Improving engineering workflows. Learning continuously.