Quality Engineering AI Lead Engineer

Requirements

• Extensive experience as a Senior QE SDET Engineeror Senior Developer
• Has breadth of experience across different tech-stacks, such as JavaScript/TypeScript, Java, C#, or Python, amongst others
• Experienced in RAG Weaviate, OpenAI, Agents, MCP, Langchain, Prompt Engineering, Browser-Use, and Django
• Experienced building AI Tools, Agents and Agentic workflows (LangGraph, CrwAI)
• Hands‑on Product building experience that cuts across the full SDLC – not just test automation and QE
• Experienced in building RAG system with a nice‑to‑have on fine‑tuning LLMs
• Cleaning/augmenting data
• Comfortable with IAS (Infra As Code) eg. giving a high‑level spec
• Fully understands test automation (across platforms and functional/non‑functional) and associated tech
• Presentation skills – C‑Suite clients and in‑house
• Mentoring – non‑AI SDETs
• Innovation – art of the possible
• Experienced in Junit, Jest, PyTest, NUnit, Appium, WDIO, Selenium, Cypress, BrowserStack, Swagger, WireMock, Postman et al
• Development frameworks: Spring, Angular, .NET, Node et al
• CI/CD: Jenkins, GitLab CI/CD, Docker/AWS, Azure DevOps
• Databases: SqlServer, MySQL, Oracle, MongoDB, H2
• BDD: Cucumber, FitNesse, SpecFlow, RestAssured, EasyB et al
• Performance: Gatling, JMeter, WebPageTest, LightHouse
• Security & code quality: SonarQube, Jacoco, PiTest, OWASP, Axe et al
• Hands on software test automation, ideally founded on a background as a senior Developer
• Experienced in building a strategy covering all aspects of the SDLC process, development, automation, CI, and metrics
• Hands on using Spring Java, Angular, Python, GitLab CI/CD, Junit, Jest, Cucumber, Bash, Gatling et al
• Experienced in helping teams evolve an Agile ‘Shift Left’ way of working
• Experience of building advanced and feature rich test automation frameworks from scratch using Object‑oriented and scripted languages
• Has a depth of knowledge in the Object‑oriented Programming paradigm (OOP) and has practically applied the principles
• Comfortable working with Git repositories and workflows on multiple tasks concurrently
• Ability to manage and lead code review processes, mitigate conflicts within the team and get quality work merged in the main branch
• Proactively collaborate with the Front‑end development team, understand the design of the Front‑end and discussing issues with the developers to better understand requirements and expectations
• Understanding of CI/CD pipelines and their importance in Automation Testing process
• Understanding of non‑functional requirements and testing, with a focus on performance (but also accessibility, compatibility and aspects of security)
• (Desirable) MCP, Django and nice‑to‑have Entra/Gunicorn
• (Desirable) GitHub Actions, GitLab pipelines, Azure DevOps pipelines, Jenkins (any experience on these will be beneficial)
• (Desirable) AWS experience
• (Desirable) Experience with any of these tools: Cypress, Playwright, Webdriver.io (but with strong experience in Selenium)
• (Desirable) Understanding (better experience) with Contract Testing frameworks (preferably PACT)
• (Desirable) Experience setting up E2E testing frameworks with automation in mind, covering all the aspects of the SDLC

What the job involves

• As a QE AI Engineer & QE Architect, you will have the opportunity of joining an award‑winning Quality Engineering team that is working on some of the most cutting‑edge technologies that is embracing new innovations, such as in‑built quality checks that embraces AI/GenAI & agentic AI across the full SDLC
• What is key to this role is the ability to lead and inspire a team, fostering a collaborative and productive work environment
• This is a hands‑on Product building experience that cuts across the full SDLC – not just test automation and QE. You will lead the expansion of our existing portfolio of Quality Engineering assets and services. Having strong verbal and written communication skills to effectively convey technical information to non‑technical stakeholders is a must
• You will join a highly focused quality engineering team that are experts in driving an AI & agentic AI engineering‑led approach to driving value for our clients. You are responsible to ensure Shift‑Left Testing emphasising early testing in the development lifecycle. You will have experience of multiple Automation Frameworks that support various types of testing
• You will play a key role as an AI mentor and train your team on the latest testing tools and methodologies
• You will always look for ways to drive SDLC efficiencies and to improve the quality engineering approach. You will have knowledge on capturing the value created through defining and tracking quality metrics

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