AI Automation Engineer (Mobile)
Release quality is not a final check — it is a continuous guarantee. This role exists to build and maintain the automation that makes that guarantee real, across Android, iOS, web, APIs and backend systems.
You will work at the intersection of conventional automation engineering and AI-native practices. That means designing frameworks that are durable and observable, while also using tools like GitHub Copilot, self-healing locator frameworks and LLM-assisted test generation to work faster and catch more.
The stakes are concrete: the journeys you protect include money movement. Regressions here cost customers directly. Your work feeds into release validation pipelines that span PRs, staging and production rollouts — feature flags, phased releases, beta builds included.
You will sit inside Qapitol's Professional Services BU, embedded with Engineering, Product and Design teams and present in Agile ceremonies. You will contribute to root cause analysis and use observability tooling — Crashlytics, Sentry, Grafana — as part of your normal workflow.
Who thrives here
You have 1–3 years of hands-on QA automation or SDET work and you are already comfortable owning a framework end to end. You do not wait to be told where coverage is thin. You are curious about AI tooling not as a novelty but as a practical accelerant. You want early, substantive exposure to how AI-native quality engineering is being built — not inherited.
What you'll own
- Design and maintain automation frameworks covering Android, iOS, web, APIs and backend systems
- Own functional, regression, integration, end-to-end and release test coverage
- Validate customer-critical money-movement journeys and perform API, backend and database verification
- Build automation suites using Java, Appium, REST Assured and TestNG; integrate with CI/CD via GitHub Actions
- Automate validation across the full delivery pipeline — from PRs through staging to production
- Own release validation for mobile builds, feature flags, beta and phased rollouts
- Perform contract testing, schema validation and non-functional testing
- Use Crashlytics, Sentry and Grafana to detect regressions and contribute to root cause analysis
- Advance AI-driven and self-healing automation practices within the team
What it takes
- 1–3 years as a QA Engineer or SDET with hands-on mobile, web and API automation
- Strong Java; practical experience with Appium, REST Assured, TestNG and Maven/Gradle
- Solid understanding of REST APIs, JSON, and request/response and schema validation
- CI/CD integration experience (GitHub Actions or equivalent) and Git version control
- Proficiency with debugging and monitoring tools: Charles Proxy, ADB, application logs, Crashlytics, Sentry, Grafana
- Fluency with AI-assisted test-authoring tools (e.g. GitHub Copilot, Testim, Mabl)
- Ability to use LLMs to generate and refine test cases from requirements or user stories
- Familiarity with self-healing automation frameworks that auto-correct broken locators
- Understanding of AI-driven anomaly detection applied to release validation and regression triage
Nice to have
- Performance testing with JMeter or K6
- Messaging systems such as Kafka or Amazon SQS
- Exposure to AWS Cloud services
- Fintech, payments or consumer-facing application experience
We respond to every application within 2 business days.