Professional summary
QA leader with 14+ years building quality engineering functions from scratch across AI tooling, AR/fashion, fitness tech, and banking. Built an 8-person QA organisation from zero in 4 months, led teams of up to 10, and increased release cadence from 2/month to as often as 4–8/month, including daily releases for one product. Combines hands-on test automation (TypeScript, Python, Java, Playwright, Appium) with quality strategy, hiring, incident management, and stakeholder leadership. Currently focused on AI-assisted testing, using coding agents, MCP servers, and BDD frameworks to scale quality as teams grow. ISTQB CTAL-TAE certified.
Experience
Zencoder
May 2025 – Present · Contract · Porto, Portugal (Remote)
Head of QA
Zencoder builds AI coding agents. As developers began shipping code several times faster, downstream testing became the delivery bottleneck. Leading a team of 4 QA engineers and 2 SDETs, reporting to the CTO, to shift QA from post-development gatekeeping to a QA Ops model where developers write their own tests with AI agent assistance.
- Redesigned the QA operating model, shifting team capacity from manual feature validation toward automation, quality infrastructure and developer enablement.
- Built BDD test frameworks, reusable prompts and Agents.md configurations that enable AI coding agents to generate and debug tests, meaningfully increasing the first-pass acceptance rate of developer-written tests.
- Rebuilt CI/CD pipelines with parallelised E2E execution (sharding) and staged sanity/smoke/regression gates, cutting total pipeline runtime from 40–60 minutes to under 25 minutes (under 15 minutes for E2E).
- Made stable E2E tests mandatory CI quality gates after reducing flaky-test failures; flaky-test rate is now tracked as an ongoing release-health metric.
- Own P0/P1 incident triage against a defined SLA (≤1 P0 per 2 weeks, ≤2 P1 per week); root cause findings feed into quality gates to prevent repeat failures.
- Introduced AI-assisted defect-to-feature traceability, reviewed monthly with the team to track quality trends by feature area.
- Enabled IDE plugin release cadence to increase from 2/month to 4–8/month, and daily releases for the new ZenFlow desktop app, both built under the new QA Ops model.
Tech stack: TypeScript, Playwright, BDD/Cucumber, Model Context Protocol (MCP) servers, AI Agents, GitHub Actions, CI/CD, Sharding
Zing Coach
Jul 2024 – May 2025 · Contract · Remote
Position: Head of QA
Head of QA for Zing AI: Home & Gym Workouts, a mobile AI fitness app (iOS, Android, web portal, AI recommendation engine, chat) rated 4.8★ on the App Store (31,000+ ratings) and 4.5★ on Google Play, with 500,000+ Android downloads. Led a team of 6 QA engineers (hired 4), reporting to the CTO and working closely with the CPO and CEO.
- Brought the team from unpredictable release timing to consistent weekly releases, acting as Release Train Manager across App Store and Google Play submissions and release documentation.
- Set up and led mobile test automation using Appium, WebdriverIO, and TypeScript.
- Wrote test strategies for iOS, Android, web, and backend, and ran the iOS automation project end-to-end.
- Built application health monitoring with on-call runbooks, giving engineers clear incident-response procedures.
- Managed third-line support and used Amplitude and customer-support data to prioritise defects by user impact rather than raw bug count.
Tech stack: TypeScript, Appium, WebdriverIO, QASE, Jira, GitHub, iOS, Android, Node.js, Amplitude
WANNA (Farfetch Group)
Mar 2022 – Jun 2024 · Full-time · Porto, Portugal
Position: Head of QA
AR fashion startup building virtual try-on technology. Built the QA department from zero to a team of 8 QA engineers (7 hired directly) within 4 months, covering multiple iOS apps, Android, a web SDK, a web app, and backend services. Reported to the CTO.
- Owned QA strategy, test management, and resource planning across all platforms; led mobile testing on native iOS and Android with Python-based backend automation.
- Integrated QA into CI/CD from the ground up, establishing automated quality gates across the full platform portfolio.
- Built a client support process connecting previously siloed hardware and software teams, working across Product Management, Development, and Client Success.
- Introduced a 3-level SLA support process, improving customer satisfaction by approximately 80% relative to baseline.
- Built a monitoring system with hourly reporting on key metrics, reducing mean time to recovery to under 2 hours per incident.
Tech stack: AWS, Python, Swift, React, Jenkins, Allure, Jira
Accenture Latvia
Jun 2015 – Feb 2022 · Full-time · Riga, Latvia
Position: Test Automation Architect (Senior QA Engineer → Lead QA → Test Architect → Automation Architect)
Nearly 7 years, promoted three times from Senior QA Engineer to Test Automation Architect, leading teams of 2–10 across banking, VoD, and big data projects.
- Built test automation frameworks across acceptance, functional, integration, contract, and E2E layers; redesigned automation strategy into a proper test pyramid, improving feedback speed and maintainability.
- Led hiring, staffing, and performance reviews in a "Three Amigos" QA environment.
- Built a reusable test framework for frontend and backend, adopted by other Accenture Riga teams.
- Held dual roles in later years: automation lead for a 3-person team, and project manager for a 20-person staff-augmentation engagement with an Irish bank.
Notable projects: staff-augmentation engagement with an Irish bank (Java, Jenkins, Allure); VoD backend platform (Java, Cucumber, AWS Lambda); big data analytics for Accenture Video Solutions (Hadoop, Hive, Qlikview).
Tech stack: Java, JUnit, Cucumber, Selenium, REST, AWS Lambda, Jenkins, Allure, Hadoop, Hive
Earlier roles
QA Engineer – Adicom Systems ·
Oct 2012 – May 2015
QA in an Agile web team building solutions for government institutions. Introduced Selenium UI test automation and owned integration, acceptance, and regression testing.
QA Engineer – DEEP 2000 ·
Nov 2011 – Sep 2012
Tested "Queue Management System" (server and client), managed pilot deployments, trained contractor staff.
Technologies
Automation: Playwright, Appium, Selenium, WebdriverIO, Cucumber/BDD, API/contract/integration/E2E testing
Languages: TypeScript, Python, Java
Delivery: GitHub Actions, Jenkins, CI/CD quality gates, test sharding, release management
Cloud & observability: AWS, Allure, application health monitoring, incident management
AI-assisted quality: AI coding agents, MCP (Model Context Protocol), agent-generated tests, prompt/agent configuration