Engineering

Automated Testing

I implemented automated testing frameworks across projects, setting up test suites that ran in CI/CD pipelines.

Used on

2023–2024

Smarter.Codes' in-house software estate behind its public site: crawler, automation framework, natural-language stack and chatbots.

2021–2025

Internal starter codebases and CI/CD tooling so new company projects skip setting up delivery from scratch.

2023–2026

Hosted self-serve platform where businesses build chatbots from visual blocks and deploy them on web, WhatsApp and Mattermost with human handover.

2021–2026

Internal engineering hiring pipeline at Smarter.Codes, run as one thread per open position with async tests before live interviews.

2022–2024

Smarter.Codes' internal estate: a MediaWiki and Wikibase documentation portal, public website and engineering consoles used by staff.

2021 · Hybrid.Chat conversational platform

Situation: The chatbot platform's runtime holds conversation state in memory, so under high availability any pod restart dropped live conversations.
Task: Survive pod churn without rewriting the conversational runtime the product was built on.
Action: I checked alternative frameworks, found the same limit, and kept the runtime: sticky sessions, state persisted to Mongo, and Redis pub/sub to close duplicates.
Result: The platform ran multi-container with state surviving restarts, and the design documented its failure modes, including those the fix introduced.

2023 · Hybrid.Chat conversational platform

Situation: The bot platform needed web push notifications, and my instinct was to build it in house for future flexibility.
Task: Decide between building and buying, separating engineering reasons from personal preference.
Action: I wrote down what I wanted from in-house, weighed it against what the release needed, and recorded the preference and the decision against it.
Result: We shipped on the vendor, and the recorded trade-off made later customisation questions easy to answer.

2026 · Engineering recruitment pipeline

Situation: Technical hiring for a research engineering role ran through me, a bottleneck and a single point of judgement.
Task: Build an interview panel that keeps the bar without depending on me.
Action: I proposed one lead and two shadows, shared candidate review beforehand, independent written feedback before discussion, and shadows who graduate into leads.
Result: The format became how the round runs, and the shadow-to-lead path grew the pool of interviewers.

2026 · Engineering recruitment pipeline

Situation: A research engineering candidate reached a working coding-round solution with AI assistance but could not explain why the Python worked.
Task: Score the round and write feedback that the candidate, recruiter and panel could all act on.
Action: I scored it low and wrote out the reasoning behind each mark, recommended not proceeding, said what to strengthen, and gave a reapplication window.
Result: The rejection was reviewable rather than a bare verdict, and the panel's differing views were visible to decision makers.