Engineering systems at Reward Gateway.
During my time at Reward Gateway, I built the delivery, analysis and evaluation systems described below, and the quality engineering function that operated them.
- Period
- 2019–2026
- Scope
- More than 200 people in product and engineering
- Role
- Head of Quality Engineering
Context
My responsibility changed over the course of my employment. I began by building the quality engineering function and its delivery systems. Later, I returned to direct technical work on production-incident analysis and release evaluation for the company’s first customer-facing AI product.
This page selects the work most relevant to the projects I take on now. It is not a complete account of the organisation or its product.
Delivery infrastructure at organisational scale
I designed the automation and measurement systems used by the function. They coordinated roughly one thousand end-to-end tests across pull-request, release and nightly runs, with the faster checks placed where they could inform a delivery decision.
I also built a library of more than seven thousand cases and linked structured test evidence to the changes being released.
Turning production incidents into engineering intelligence
I built a Python pipeline across the company’s incident tracker, documentation and monitoring systems to analyse 451 production incidents over ninety days.
The analysis found that 61 per cent could have been prevented through testing and that root cause was recorded on fewer than one in twenty incidents. It supported a £227,000 annual business case for preventable failure. This was a costed business case, not a claim that the amount had already been saved.
Evaluation and security for a customer-facing AI product
I took hands-on responsibility for quality and release evaluation on a multi-tenant retrieval assistant built with AWS Bedrock and OpenSearch across web, iOS and Android.
I created the evaluation and adversarial security testing from nothing. It covered answer quality, prompt injection, tenant isolation, personal data and retrieval scope. I recorded the limits of the testing alongside its findings so the release panel could make its decision with the remaining risks visible.
Building the capability around the systems
I built the quality engineering function from zero to fifteen engineers across London and Sofia, supporting more than two hundred people in product and engineering.
I also designed its career framework so senior engineers could progress without leaving technical work and ran an intern programme.
Results
- Delivery infrastructure coordinating roughly one thousand end-to-end tests.
- More than seven thousand cases connected to release evidence.
- An incident-analysis pipeline that supported a £227,000 annual business case.
- Evaluation and adversarial security coverage used for the company’s first customer-facing AI product.
- A quality engineering function grown from zero to fifteen engineers.