Quality Assurance Analyst

We are seeking a forward-thinking QA Analyst to join our engineering team. The ideal candidate brings a modern quality mindset - one that blends traditional QA rigor with AI-assisted tooling, intelligent test automation, and a shift-left approach embedded throughout the software development lifecycle. You'll work alongside developers, product managers, and AI systems to deliver exceptional software quality at speed. Key Responsibilities 1. AI-Augmented Test Design: Leverage AI tools (e.g., GitHub Copilot, Testim, Mabl, or similar) to generate, maintain, and optimize test cases - reducing manual authoring time and expanding test coverage. 2. Shift-Left Quality: Embed quality practices early in the development cycle by collaborating with product and engineering during requirements and design, catching defects before code 3. Automated Testing: Design, build, and maintain end-to-end automated test suites using frameworks like Selenium, Playwright, or Cypress, integrated into CI/CD pipelines. 4. AI Flow Integration: Validate and test AI-powered features and workflows within the product including prompt behavior, model outputs, edge cases, and integration with LLM APIs ensuring reliability and accuracy. 5. Defect Management: Identify, document, and prioritize defects using Jira; partner closely with developers using data from AI-assisted root cause analysis tools to drive faster 6. Functional & Non-Functional Testing: Execute functional, regression, integration, performance, and exploratory testing across web, mobile, and API surfaces. 7. CI/CD Quality Gates: Maintain and improve automated quality gates within Jenkins, GitHub Actions, or similar pipelines to enforce code quality on every build. 8. Data Validation: Ensure data integrity through SQL queries, API response validation, and schema checks including validation of AI model inputs and outputs. 9. Test Strategy & Documentation: Author and maintain living test plans, test strategies, and runbooks that reflect modern, AI-assisted workflows. 10. Continuous Improvement: Actively monitor QA metrics (defect escape rate, test coverage, automation ROI) and use AI-driven analytics to identify trends and improve quality processes Mandatory Skills & Qualifications 1. Automation Expertise: Hands-on experience building and maintaining automated test suites. Proficiency with Selenium required; experience with Playwright or Cypress a strong plus. 2. AI Tool Proficiency: Demonstrated experience using AI-powered development or testing tools (e.g., GitHub Copilot, Testim, Mabl, ChatGPT for test scripting, or similar) to accelerate for test automation and scripting. 4. API Testing: Experience testing REST APIs using tools like Postman, RestAssured, or similar. 5. CI/CD Integration: Familiarity with Jenkins, GitHub Actions, or similar pipelines for integrating and running automated tests. 6. Database Knowledge: Proficiency in SQL for data validation and backend verification. 7. Agile & DevOps Mindset: Strong understanding of Agile/Scrum workflows and DevOps 8. Jira: Experience with Jira for defect tracking, sprint ceremonies, and test management integrations. 9. Debugging Skills: Strong ability to isolate, reproduce, and communicate root causes of AI & Emerging Skills (Preferred) 1. LLM/AI Feature Testing: Experience validating AI-generated outputs, prompt chains, or LLM-integrated workflows for accuracy, hallucination, bias, and edge-case behavior. 2. AI Test Generation: Familiarity with tools that auto-generate test cases from user stories, code diffs, or acceptance criteria using machine learning. 3. Observability Tools: Experience with monitoring and log-based tools (e.g., Datadog, Splunk, Grafana) to support AI flow validation and regression detection in production. 4. Cloud Platforms: Exposure to AWS, Azure, or GCP for testing cloud-hosted and distributed systems. 5. Containerization: Basic understanding of Docker and Kubernetes for running tests in isolated, reproducible environments. 6. Unix/Linux: Comfort navigating Linux environments and writing shell scripts. 7. Git: Proficiency with Git version control, branching strategies, and PR-based workflows. Key Attributes 1. A quality-first mindset - you advocate for the end user in every sprint. 2. Curious and adaptable: you embrace AI tools as force multipliers, not replacements for critical thinking. 3. Strong communicator who can translate technical defects into clear, actionable language for stakeholders at all levels. 4. Data-driven: you make decisions grounded in metrics, coverage reports, and test analytics. 5. Collaborative team player who thrives in cross-functional squads with engineers, PMs, and designers. Qualifications Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent practical experience). Minimum of 3 years of experience in software QA, with at least 1 year involving automation or AI-assisted testing. Why Join Us? Work with Modern Technology: You'll test and shape real AI-powered product features - not just legacy CRUD apps. Invest in Your Growth: Access to training, certifications (ISTQB, AWS, AI tooling), and conference opportunities to keep your skills current. Collaborative Culture: A supportive, inclusive team where your voice matters and quality is everyone's responsibility. Work-Life Balance: Flexible arrangements and a genuine commitment to sustainable pace. Competitive Compensation: Attractive salary, performance bonuses, and comprehensive Wellness & Inclusion: Mental health resources, fitness programs, and a diverse workplace where every background is valued. If you're passionate about quality and excited to work at the intersection of software engineering and artificial intelligence, we'd love to hear from you. #J-18808-Ljbffr