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# Automation Test Engineer

- **Company:** Accenture
- **Location:** Slough, UK
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Test Suite, Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Automation of Tests, Cloud Computing, Cloud Engineering, Code Coverage, Encodings, Computer Programming, Continuous Integration, Object-Oriented Software Development, Systems Development Life Cycle, Oop Languages, Selenium, Test Case, Test Data, Test Execution Engine, Cloud Platform System, Postman, Large Language Models, Cypress (Programming Language), Playwright, Data Analytics, Virtual Agents, Functional Programming, Restful APIs, GPT
- **Published:** August 6, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/x/42187845/

## About the Role

Skills & Experience 2+ Years Experience: Proven track record in Quality Engineering / Technical Testing rolesShift Left Expertise: Experience engaging early in SDLC (e.g., Three Amigos), with exposure to AI-assisted requirement/test analysisManual & Exploratory Testing: Strong experience in designing exploratory test charters, ideally enhanced with data-driven or AI-supported techniquesOOP & Programming: Solid understanding of OOP (Classes, Methods, Inheritance) with proficiency in Java or PythonAutomation Tools: Hands-on experience with frameworks like Playwright, Selenium, or CypressAI-Augmented Testing Exposure: Working knowledge or hands-on exposure to AI-based test generation tools, self-healing automation, LLM-assisted scripting or debuggingIndependence: Ability to manage workstreams and collaborate effectively with minimal supervisionAPI Testing: Experience testing REST APIs using tools like Postman or automation frameworks
Desirable Skills (The Competitive Edge) Cloud Proficiency: Experience with AWS or GCP (e.g., S3, EC2, Lambda, GKE)Agentic AI Exposure: Experience or strong interest in:Autonomous testing agentsAI-driven test orchestrationPrompt engineering for QA use casesAI Tooling Ecosystem: Familiarity with tools/platforms such as:LLMs (e.g., GPT-based tools)AI test platforms (e.g., self-healing frameworks, intelligent test optimisation tools)Data-Driven QA: Experience using test analytics, predictive quality metrics, or AI dashboardsContinuous Learning Mindset: Demonstrated curiosity and experimentation with AI in QA
What's in it for you

## Description

As an AI Quality Engineer, you will act as a proactive consultant, embedding a Shift Left and AI-first mindset across the entire SDLC. You will embed quality early by preventing defects during requirements and design, leveraging AI-driven and Agentic testing approaches to enhance speed, accuracy, and scalability.
You will utilise your expertise in Cloud environments (AWS/GCP) and Object-Oriented Programming (OOP) to build intelligent, scalable automation solutions, while actively driving the adoption of AI-powered testing tools, autonomous test agents, and data-driven quality insights to modernise the testing lifecycle for our clients.
Key Responsibilities Embeds Shift Left & AI-Assisted Quality Practice by engaging in quality discussions during requirements and design phases, test case generation and risk identification to prevent defects before development begins. This allows for testing the idea before it becomes code.Executes Intelligent Exploratory Testing, designs and performs advanced exploratory testing charters augmented by AI-driven insights and heuristics to identify risks, edge cases and hidden defects in complex architectures.Develops Automation with OOP & AI Augmentation. Builds and maintains modular, reusable automated test frameworks (e.g. Playwright, Selenium, Cypress) incorporating AI-assisted script generation, self-healing automation frameworks and test optimisation using ML-based feedback loops. OOP principles are applied to create clean, maintainable and scalable test code in Java or Python.Leverages Cloud & AI-Integrated Test Infrastructure. Operates within AWS/GCP environments to
execute cloud-native and distributed test execution, manage test data pipelines and monitor logs and quality signals within CI/CD pipelines.Drives Agentic AI in Testing. Designs, implements and experiments with Agentic AI testing solutions including autonomous test agents that generate, execute and adapt tests, AI-driven defect prediction and root cause analysis, intelligent test suite prioritisation and optimisation and continuous learning systems that improve test coverage over time.Improves Client Delivery with AI Insights. Identifies bottlenecks in delivery pipelines and leverages AI-driven analytics and predictive insights to recommend strategic QA improvements, enhancing deployment speed, quality and stability.Maintains Strategic Interlock Across Teams. Collaborates independently with cross-functional teams and insights to strengthen feedback loops between developers, product owners and stakeholders.


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