Lead AI-Driven QA Automation Engineer

Rothstein Recruitment

England

On-site

GBP 90,000 - 135,000

Full time

42 hours ago

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Job summary

Rothstein Recruitment is seeking a Principal QA Automation Engineer for a Payments FinTech with AI ambitions. The role is hands-on and senior, responsible for building automation and quality engineering across a complex platform.

You will design scalable API and integration tests, establish QA metrics, explore AI-driven testing and AI-powered QA agents, and lead engineering standards while contributing as an individual contributor.

Qualifications

7+ years of experience in QA Automation / Quality Engineering with hands-on engineering
Proven ability to build automation frameworks and QA capabilities from scratch
Deep experience with API automation, integration testing and contract testing
Strong understanding of CI/CD and automated quality engineering
Experience with Jenkins, GitHub Actions, GitLab CI or equivalent
Experience building, integrating or experimenting with AI agents, LLM-based tooling or agentic workflows
Ability to work independently, take ownership and make technical decisions without significant management oversight

Responsibilities

Build the QA automation strategy and technical capability across the payments platform.
Design and develop scalable automation frameworks for API, integration, contract and end-to-end testing.
Build automation from the ground up using Java/JVM, Golang, REST Assured, Postman/Newman and internal tooling.
Own the quality and automation metrics across the platform, defining what should be measured and how those metrics are used to improve engineering quality.
Establish meaningful measures around automation coverage, defect trends, test effectiveness, reliability, flakiness, execution performance and release quality.
Build automated quality gates and integrate them into CI/CD pipelines.
Identify opportunities to use AI and LLMs to improve the QA lifecycle, from test generation and analysis through to defect detection and investigation.
Design, build and test AI-powered QA agents capable of performing testing, analysing results, identifying anomalies and supporting engineering teams.
Establish approaches for testing AI agents, including accuracy, reliability, robustness, hallucination, regression and behavioural testing.
Build frameworks and tooling that allow AI-driven testing capabilities to be repeatable, measurable and production-ready.
Work closely with engineers to improve testability, observability and quality at source.
Establish engineering standards for automation code, framework design, test data, CI/CD and quality reporting.
Provide technical leadership through design reviews, code reviews and mentoring, while remaining a hands-on individual contributor.