QA Automation Engineer

Margins is an award-winning AI and software engineering company helping organizations turn AI opportunities into production-ready solutions and measurable business outcomes. We work across the full AI delivery lifecycle - from strategy and discovery through custom AI/software development, deployment and ongoing optimization. Our teams build complex web and mobile platforms, enterprise software, AI agents, LLM applications, RAG systems, workflow automation and other production-grade AI solutions for clients across the US and Europe. We are looking for an experienced Test Automation Engineer who believes AI is fundamentally changing how software quality should be done. The Role We are looking for someone who combines strong software testing fundamentals with automation engineering and an AI-first approach to QA. You will work across Margins and client projects to establish testing strategies, build automated testing infrastructure and help engineering teams ship high-quality software faster. We expect you to actively use modern AI development tools to multiply your effectiveness — generating and maintaining automated tests, identifying edge cases, analyzing failures, creating test data, understanding unfamiliar codebases and eliminating repetitive QA work. The goal isn’t to automate everything. The goal is to determine what should be tested, what should be automated and how AI can make the entire quality process dramatically more efficient. What You’ll Do Own Quality Establish QA processes and testing strategies on new client projectsUnderstand complex product workflows and identify the highest-risk areasDefine test plans, regression strategies and release criteriaPerform exploratory and risk-based testing where human judgment provides the most valueImprove release confidence without unnecessarily slowing engineering velocityCommunicate quality risks clearly to engineering teams, product managers and clients Build Test Automation Design, build and maintain automated E2E and regression test suitesAutomate testing and validationCreate reusable testing infrastructure across projectsIntegrate automated tests into CI/CD pipelinesImplement appropriate release gates and automated quality checksIdentify flaky tests and continuously improve automation reliability Use AI as a QA Multiplier We specifically want someone who actively experiments with how AI can improve software testing. You should be comfortable using tools such as Claude Code, Cursor, Codex, GitHub Copilot or similar AI development tools to: Generate automated tests from requirements, user stories and existing codeGenerate boundary conditions and unexpected edge casesCreate realistic test data and test fixturesAnalyze failed tests, logs and stack tracesAccelerate root-cause investigationMaintain and refactor existing automation suitesConvert discovered bugs into permanent regression testsReduce repetitive manual QA workExplore autonomous and agent-based QA workflows We don’t expect a specific AI tool. We care about whether you have developed an AI-native way of working and can demonstrate that AI meaningfully increases your output. Test Modern Applications Depending On The Project, You May Work Across Complex web applicationsMobile applicationsREST and GraphQL APIsMicroservicesSaaS platformsEnterprise integrationsReal-time workflowsCloud infrastructureAI-powered applications You should be comfortable validating not only what appears on screen but also what happens underneath it. Help Us Test AI All Margins’ work involves AI systems. You will help us develop even better approaches for testing: LLM applicationsRAG and enterprise knowledge systemsAI agents and multi-step agentic workflowsPrompt and model regressionsStructured LLM outputsHallucination and groundednessAI workflow reliabilityTool/function callingAI-generated outputs against expected criteriaEvaluation datasets and automated AI evals Previous AI/LLM testing experience is a strong advantage, but deep curiosity and the ability to rapidly learn this emerging discipline are equally important. What We’re Looking For Must Have 2+ years of experience in software QA, test engineering or test automationStrong understanding of software testing fundamentalsStrong experience with automated testing of modern web applicationsHands-on experience with Cypress, Selenium or similar frameworksAbility to write clean automation code in TypeScript/JavaScript, Python or another modern languageExperience testing REST APIsExperience with Postman or similar API testing toolsStrong regression and exploratory testing skillsExperience working with GitUnderstanding of modern software development and release processesStrong debugging and root-cause investigation skillsAbility to independently understand complex product workflowsStrong written and verbal EnglishAbility to work autonomously and take ownership of quality Strong Advantages Deep test automation experienceCI/CD testing experience with GitHub Actions, GitLab CI, Jenkins or similarSQL/database testing experienceAWS or Azure experienceDocker experienceExperience with Sentry, CloudWatch or similar monitoring/logging platformsPerformance/load testing experienceExperience testing enterprise integrationsExperience working directly with clientsStartup or fast-moving product development experienceClaude Code, Cursor, Codex, GitHub CopilotAI-assisted test generationAI-assisted debuggingAgentic development workflowsAutomated browser agentsLLM evaluation frameworksRAG/LLM testingPrompt regression testing How We Work We value people who: Think like engineers, not test-script executorsTake ownership instead of waiting for detailed instructionsUnderstand that quality is a team responsibilityChallenge inefficient processesExperiment with new toolsAutomate repetitive workCommunicate problems together with potential solutionsAre comfortable working across different technologies, products and industries