I build scalable, production-grade systems across application, data, and infrastructure layers.

My work focuses on distributed systems, high-volume data processing, platform reliability, and designing software that behaves predictably under real-world conditions.

I prefer understanding systems deeply rather than treating them as black boxes. Whether it's debugging, performance tuning, or designing new components, I focus on how things behave under load, across environments, and when failures occur.

I tend to take a pragmatic approach balancing ideal architecture with real-world constraints to build solutions that are reliable, maintainable, and efficient.

I use AI tools primarily for efficient research and exploration, but I design and implement solutions myself. For me, understanding how a system works end-to-end is essential to maintaining and evolving it, especially when working on complex or high-scale systems.

• Distributed systems and asynchronous processing
• Data pipelines and high-volume processing
• System performance and optimisation
• Multi-tenant architectures
• Efficient containerised environments (Docker)
• Infrastructure as Code with Terraform and AWS
• Python & Django applications