QA Automation Engineer

Accountabilities: Participate actively in requirements refinement, technical handoffs, and functional discussions to identify risks, ambiguities, dependencies, and quality gaps early in the development process. Analyze PRDs, Epics, User Stories, acceptance criteria, Figma designs, and technical documentation to understand functional and business flows. Translate product and business requirements into clear, prioritized, traceable, and sustainable test strategies and scenarios. Identify positive, negative, alternative, edge-case, integration, and high-risk scenarios. Define validation strategies based on risk and impact, determining when manual testing, automation, or a hybrid approach is most appropriate. Promote a QA Early approach by helping prevent defects before implementation and reducing reliance on end-of-cycle validation. Collaborate closely with Engineering, Product, DevOps/SRE, and other teams throughout the delivery lifecycle. Develop, maintain, and evolve automated UI and API tests, prioritizing critical and high-risk workflows. Contribute to automation framework architecture, engineering standards, reusability, maintainability, and separation of responsibilities. Conduct code reviews for automation and assess Pull Requests and technical changes for potential quality impacts and additional validation needs. Establish appropriate Smoke, Sanity, and Regression testing strategies based on change criticality, risk, and business impact. Investigate and reduce flaky tests to improve the reliability and stability of automated test suites. Integrate automated testing into CI/CD pipelines and monitor execution and results. Follow initiatives through production deployment, including validation of Feature Flags, integrations, configurations, and dependencies. Support production incidents through troubleshooting, root-cause analysis, and definition of preventive actions. Use logs, metrics, and observability tools to investigate and diagnose technical and quality issues. Leverage AI tools to support requirements analysis, risk identification, test design, automation, troubleshooting, and documentation while critically reviewing outputs and protecting sensitive information. Identify and contribute to the management of Quality Debt and Automation Debt based on business risk, impact, and priorities. Monitor quality and engineering metrics to identify opportunities for process improvement and greater delivery reliability. Provide technical guidance and knowledge sharing to Junior and Mid-Level QA professionals. Communicate quality risks, impacts, blockers, and recommendations clearly to Product, Engineering, and other stakeholders. Work autonomously and collaboratively while balancing quality, risk, delivery speed, and business needs. Requirements: Solid experience as a QA Engineer, Quality Engineer, or in a similar role within software development and agile environments. Strong experience in requirements analysis and Test Design, translating functional and technical documentation into comprehensive test flows and scenarios. Ability to interpret PRDs, Epics, User Stories, acceptance criteria, Figma designs, and technical documentation. Proven experience defining and prioritizing positive, negative, alternative, edge-case, and integration scenarios. Strong practical knowledge of BDD and Gherkin , including Features, Scenarios, Scenario Outlines, and Given/When/Then structures. Hands-on experience with test automation, regardless of programming language or framework. Experience automating both UI and API tests . Strong knowledge of REST APIs, including HTTP methods, status codes, headers, payloads, authentication, and contracts. Understanding of automation framework architecture and software engineering principles such as abstraction, reusability, maintainability, and separation of responsibilities. Experience with Git, Pull Requests, branching strategies, and code reviews. Experience using databases and SQL queries for data validation and troubleshooting. Experience integrating and executing automated tests within CI/CD pipelines. Ability to investigate automation failures and distinguish between flaky tests, environmental issues, data problems, and product defects. Knowledge of Smoke, Sanity, and Regression testing strategies. Understanding of distributed systems, APIs, integrations, and microservices sufficient to identify risks and define appropriate validation strategies. Ability to interpret logs and use observability tools for troubleshooting. Strong understanding of the software development lifecycle from refinement through production. Ability to assess changes critically and determine what to test, how to test it, when to automate, and the appropriate level of coverage based on risk. Knowledge of agile methodologies, particularly Scrum and Kanban. Experience participating in refinements, estimations, planning, and initiative tracking. Ability to work effectively with incomplete or ambiguous requirements while proactively seeking clarification and identifying risks. Strong prioritization skills, with the ability to balance validation needs against risk, business criticality, impact, and available time. Knowledge of quality and engineering indicators such as Defect Escape Rate, automation coverage, suite stability, Flaky Rate, rework, Lead Time, and Cycle Time. Understanding of DORA Metrics and their relationship to delivery quality, stability, and reliability. Ability to use metrics as tools for diagnosis and continuous improvement rather than individual performance measurement. Strong organization, autonomy, accountability, and prioritization skills. Excellent communication and collaboration skills across QA, Engineering, Product, DevOps/SRE, and business teams. Empathy, resilience, and a constructive approach to working across different teams and technical contexts. Preferred / Nice to Have: Experience with TypeScript for test automation. Experience with C# and .NET/.NET Core for automation, testing, or application integration. Experience with modern automation frameworks such as Playwright, Selenium, Cypress, or equivalent technologies. Experience with GCP and/or AWS. Knowledge of Docker, Kubernetes, and containerized environments. Experience with distributed systems and microservices architectures. Experience with messaging and event-driven architectures using Kafka, RabbitMQ, or similar technologies. Knowledge of Redis and caching strategies. Knowledge of API Gateway and API management. Experience with highly available, high-volume, or business-critical applications. Experience with performance and load testing. Experience with contract testing. Knowledge of deployment strategies such as Canary, Blue/Green, Rollback, and Feature Flags. Experience with observability platforms such as Datadog, Grafana, Prometheus, CloudWatch, or equivalent tools. Experience with SRE practices and indicators such as SLI, SLO, and SLA. Experience working with e-commerce, logistics, payments, marketplaces, SaaS, or integration platforms. Experience working with multidisciplinary teams and products involving multiple integrations. Experience with security testing or knowledge of authentication, authorization, and API protection concepts. Experience applying AI tools to Quality Engineering and Test Automation. Experience contributing to the evolution, modernization, or restructuring of automation frameworks. Benefits: 100% remote working arrangement from Brazil. Full-time employment opportunity. International working environment. Opportunity to work across the full software development lifecycle and influence quality from requirements through production. Exposure to modern test automation, CI/CD, cloud, observability, distributed systems, and AI-assisted quality engineering practices. Opportunity to contribute to automation architecture, engineering standards, and continuous improvement initiatives. Collaboration with multidisciplinary Engineering, Product, DevOps/SRE, and QA teams. Technical ownership and opportunities to share knowledge and support the development of other QA professionals.