Lead Platform & Security

About Shuttlers

Shuttlers is a shared-mobility platform moving commuters across Lagos and Abuja. Riders and drivers depend on our web and mobile apps to book, track and pay for trips every day, so every release has to work for the people who rely on it to get to work.

Our engineering team ships often across web, mobile and backend, but most of our testing is still manual. We now need someone to build automated quality checks into CI/CD and make quality visible across the team.

The role

You will lead QA for Shuttlers Engineering, reporting to the Head of Engineering and managing a team of 1–2 QA engineers. You will work closely with the product squads (web, mobile and backend), SRE and Product leadership.

You are a risk advisor, not a gatekeeper. Your job is to make quality visible so Engineering and Product can make informed release decisions.

This is a player-coach role with three parts, and all of them matter: you are a hands-on individual contributor, a people manager and a mentor. You will own our test tooling decisions and write much of the framework and test code yourself, while growing your QA engineers, and the developers around them, into strong automation engineers. With a small team, we value pragmatic choices: proven tools, simple designs and custom builds only where they clearly pay off. Because AI tools are part of how we work, we expect a faster pace than a traditional automation rollout, and our 90-day goals reflect that.

What you will doTest automation*

• Architect and build test frameworks. Design and implement automated UI testing for our web (JavaScript/TypeScript) and mobile (Flutter) apps, starting with critical rider and driver journeys.
• Own API and contract testing. Build automated API test suites for our backend services and introduce contract testing between services and their clients, so breaking changes are caught before they reach the apps.
• Simulate real-world conditions. Test the way our users actually ride: GPS and location changes along a route, slow or dropped networks, background and resume, and a realistic spread of Android and iOS devices, including low-end Android.
• Use AI-assisted tooling. Use AI tools heavily to generate, maintain and refactor test scripts and pipeline code, with human review of every test that gates a release.

Environments and delivery

• Own test environments and data. Define how test environments are provisioned and kept stable, manage seeded test data, and make OTP, email and SMS flows testable end to end.
• Integrate with CI/CD. Run the right suites at the right stage (pull request, merge, pre-release) so quality checks protect releases without slowing them down.

Quality and release risk

• Act as a risk advisor. Track defects, assess the impact of production issues, and give Engineering and Product leaders the data they need for go/no-go release decisions.
• Measure what matters. Define, track and report escaped defects by severity per release, coverage of critical rider and driver journeys, flaky test rate, pipeline duration, mean time to detect regressions and the share of new tests written by developers. Use these metrics to guide where the team invests.
• Build a Quality Enablement model. Make our frameworks easy enough that web, mobile and backend developers write and own tests for their own features.

Leadership

• Lead the QA team. Manage 1–2 QA engineers: set clear goals, run regular 1:1s, and own their performance and growth.
• Stay hands-on. Spend a substantial part of every week writing, reviewing and maintaining test code yourself, and set the standard for test design, code quality and pipeline work.
• Mentor and grow. Mentor your QA engineers through pairing and code review as they move from manual testing to writing, maintaining and owning automation, and coach developers on good testing practice.

Our stack

We build web apps in JavaScript/TypeScript and mobile apps in Flutter, and deliver through GitHub CI and ArgoCD.

Area

What we run

Web

JavaScript/TypeScript

Mobile

Flutter apps for Android and iOS

Delivery

GitHub CI, ArgoCD (GitOps), Kubernetes

Observability

OpenTelemetry, SigNoz

Test tooling

Playwright for web and Maestro for Flutter (current preference; you will own the final choice)

Requirements What we are looking forMust have*

• 5+ years in QA or SDET roles, including 2+ years leading test automation.
• Proven experience setting up a QA automation framework from scratch for both web and mobile apps, and running it in CI/CD as the team's main way of testing.
• A track record of turning manual test cases for web and mobile into codified, automated test scripts, with more than 90% of test cases automated in a previous role.
• Evidence that your framework eliminated or sharply reduced regressions, and that you tracked them, for example through escaped regressions per release or time to detect a regression falling over time.
• Hands-on expertise with at least one modern web automation tool (e.g. Playwright, Cypress) and one mobile testing framework (e.g. Maestro, Appium).
• Experience building automated API tests and working with service contracts (e.g. OpenAPI, Pact or similar).
• Strong coding skills in JavaScript/TypeScript.
• Experience building and maintaining CI/CD pipelines (e.g. GitHub Actions, GitLab CI).
• Experience managing test environments and test data.
• Experience managing and mentoring QA engineers, including growing manual testers into automation roles, while staying hands-on in the code yourself.
• A pragmatic, data-driven approach to quality: you know how to balance shipping fast with shipping reliably.

Nice to have

• Experience with Dart and Flutter testing.
• Experience with location simulation, network throttling or device farms (e.g. BrowserStack, Firebase Test Lab).
• Experience using AI-assisted tools for test generation or maintenance.
• Performance or load testing experience (e.g. k6, Gatling).
• Background in mobility, logistics or payments products.

Your first 90 days

By day 30: you have audited current testing, environments and the release flow, agreed tooling and the list of critical rider and driver journeys with Engineering and Product, and baselined the quality metrics. The framework is set up for web and mobile, the first critical journeys are automated and running on every pull request, and you are using AI-assisted tools to convert existing manual test cases into automated scripts.

By day 60: all critical rider and driver journeys on web and mobile are automated, with API and contract tests for the services behind them, all running in CI/CD. Most of the existing manual regression suite is automated, test environments and seeded data are stable, and OTP, email and SMS flows are testable end to end.

By day 90: more than 90% of regression test cases are automated, the flaky test rate is tracked and kept low, and real-world condition scenarios (location changes, poor networks, low-end devices) are in place. A regular quality report shows regression trends to Engineering and Product, each QA engineer owns part of the suite, and developers have started writing tests for their own features.

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