Automation Test Engineer - AI
Job Description
Role: Automation Test Engineer - AI Role Location: London, Birmingham, Bristol, Manchester Salary: Competitive (based on experience) Level: CL9 - Consultant Please Note: Any offer of employment is subject to satisfactory BPSS and SC security clearance which requires 5 years continuous UK address history (typically including no periods of 30 consecutive days or more spent outside of the UK) and declaration of being a British passport holder with no dual nationalism at the point of application. Note: The above information relates to a specific client requirement Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge. We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People, Client Value Creation, One Global Network, Respect for the Individual and Integrity. Year after year, Accenture is recognized worldwide not just for business performance but for inclusion and diversity too. “Across the globe, one thing is universally true of the people of Accenture: We care deeply about what we do and the impact we have with our clients and with the communities in which we work and live. It is personal to all of us.” - Julie Sweet, Accenture CEO Qualification About usSecure Transformation Services is the UK market leader for sovereign tech transformation for secure clients working on projects in complex regulated public sector environments. Our engineering teams delivercutting-edgesolutions that empower organisations to tackle complex challenges modernise infrastructure and drive transformative growth. We provide bespoke software solutions that enable organisations to meet customer demands modernise critical infrastructure and accelerate time-to-market. By applying Secure by Design principles andleveragingAgile frameworks DevOps best practices and cloud-native architectures we ensure compliance with technical standards regulatory requirements and organisational goals. The scale of our capabilities and client engagements and our collaborative approach tooperatingand delivering valueprovidean unparalleled opportunity for growth and advancement. The Role As an AIQuality Engineer, you will act as a proactive consultant, embedding a Shift Left and AI-first mindset across the entire SDLC. You willembed quality early by preventing defects during requirements and design,leveragingAI-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 toidentifyrisks, edgecasesand hidden defects in complex architectures.
- Develops Automation with OOP & AI Augmentation. Builds andmaintainsmodular, 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,maintainableand 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 andmonitorlogs and quality signals within CI/CD pipelines.
- Drives Agentic AI in Testing. Designs,implementsand experiments with Agentic AI testing solutions including autonomous test agents that generate,executeand 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.Identifiesbottlenecks in delivery pipelines and leverages AI-driven analytics and predictive insights to recommend strategic QA improvements, enhancing deployment speed,qualityand stability.
- Maintains Strategic Interlock Across Teams. Collaborates independently with cross-functional teams and insights to strengthen feedback loops between developers, productownersand stakeholders.
- 2+Years Experience: Proventrack recordin Quality Engineering / Technical Testing roles
- Shift Left Expertise: Experience engaging early in SDLC (e.g., Three Amigos), with exposure to AI-assisted requirement/test analysis
- Manual & Exploratory Testing: Strong experience in designing exploratory test charters, ideally enhanced with data-driven or AI-supported techniques
- OOP & Programming: Solid understanding of OOP (Classes, Methods, Inheritance) withproficiencyin Java or Python
- Automation Tools: Hands-on experience with frameworks like Playwright, Selenium, or Cypress
- AI-Augmented Testing Exposure: Working knowledge or hands-on exposure toAI-based test generation tools,self-healing automation,LLM-assisted scripting or debugging
- Independence: Ability to manage workstreams and collaborate effectively with minimal supervision
- API Testing: Experience testing REST APIs using tools like Postman or automation frameworks
- Cloud Proficiency: Experience with AWS or GCP (e.g., S3, EC2, Lambda, GKE)
- Agentic AI Exposure: Experience or strong interest in:
- Autonomous testing agents
- AI-driven test orchestration
- Prompt engineering for QA use cases
- AI 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 dashboards
- Continuous Learning Mindset: Demonstratedcuriosity and experimentation with AI in QA
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