Senior QA Automation Engineer

We're looking for a Senior QA Automation Engineer to join our team in Malaga, Spain in a hybrid working mode. This role blends the strengths of a Senior QA Engineer with those of a Software Developer in Test, enhanced for the AI era. You will combine deep testing expertise with strong engineering skills, building automation frameworks, integrating quality into CI/CD pipelines, and designing advanced test strategies for both traditional and AI-powered software systems.

This is your opportunity to lead quality engineering initiatives in a cutting-edge environment where cloud, automation and AI-driven systems intersect, ensuring the reliability and safety of next-generation applications.

Analyze requirements and architecture to create comprehensive test plans, cases and data sets across functional, integration, regression and exploratory testing Design and maintain automation frameworks using tools such as Cypress, Playwright, Selenium, JMeter, Gatling Develop and integrate testing tools into CI/CD pipelines to boost engineering productivity Build observability and telemetry solutions for real-time quality monitoring Identify and automate repetitive tasks, reducing manual testing effort Manage defect lifecycle: reproduce, isolate, document and prioritize issues until resolution Apply AI-assisted workflows for test generation, code review and defect triage, while validating AI outputs for accuracy Design and execute targeted testing for AI/LLM-powered features, including safety and reliability checks Collaborate with developers for quality-first practices across the SDLC and provide leadership in quality strategy Work within an agile delivery model, contributing to process improvements and mentoring team members Strong experience in software quality assurance covering UI/black-box testing and white-box techniques Proficiency in at least one programming language (Java, Python, Scala, or TypeScript) Hands-on experience with automation tools (e.g., Cypress, Playwright, Selenium) Understanding of SDLC, STLC and agile practices Proven experience with CI/CD systems (e.g., GitLab, Jenkins, Azure DevOps, Argo CD) Knowledge of cloud services and container platforms (AWS, Azure, GCP, Kubernetes, Docker) Familiarity with observability tools (Splunk, Grafana, Prometheus, Datadog) Practical experience with AI coding assistants (e.g., GitHub Copilot, Claude Code) for test authoring and debugging Familiarity with testing AI features, including evaluation harnesses, golden-set tests, prompt injection safeguards, and model regression strategies Awareness of responsible AI principles: bias, fairness, privacy and safety considerations Experience designing and validating prompts, LLM workflows, and automation environments with AI integration Excellent communication abilities for bug reporting, test planning, and explaining quality trade-offs. Strong analytical and problem-solving skills Experience with performance testing (e.g., Gatling, JMeter) Prior leadership experience in QA teams or test strategy definition Experience in highly regulated or data-sensitive environments