**Overview of the Position** As a highly skilled professional, you will be responsible for leading and overseeing the development of comprehensive test strategies across different layers in the testing pyramid. The ideal candidate will have a strong background in software development life cycle (SDLC), Agile methodologies, and Quality Assurance or Quality Engineering methodologies. You will also be expected to have excellent technical skills with REST APIs, data, pipelines, and backend services. **Responsibilities** - Architect and oversee end-to-end test strategies across different layers in the testing pyramid; - Define, evaluate, and monitor model validation criteria, including accuracy threshold, confidence scoring, fallback behaviors, etc.; - Drive the automation of QA processes, ensuring robust, scalable processes for data ingestion, extraction, and classification; - Lead the validation integration points between AI components and business logic, identifying risks and ensuring seamless operation; - Own, maintain, and evolve the test infrastructure, specifically the CI/CD quality gates, data generation, and automated validation scripts; - Establish and monitor key quality metrics aligned with the business goals, including turnaround time, confidence scores, and user corrections; - Act as a strategic partner to Product and Engineering, and advocate for quality from design through delivery; - Keep up with the latest AI tech and how to best apply the latest advancements to make the previously impossible possible for our customers; - Sense of ownership, take ownership of code quality through exploratory and automated tests. **Requirements** - 5+ years in AQA, Software Test Engineering, or related roles, including leadership responsibilities; - Experience in AQA Javascript; - Proven experience building and scaling test automation frameworks (e.g., Pytest, Cypress, Selenium, Postman, etc.); - Strong technical background with APIs, CI/CD pipelines, backend services, and cloud environments (AWS, Azure); - Exceptional attention to detail, with a mindset for building robust systems that catch issues early and protect the customer experience; - Demonstrated fast, proactive learning skills, especially crucial in the rapidly changing field of AI; - Uppper-Intermediate English level. **Nice to Have** - Experience testing AI/ML in production environments; - Experience with GenAI model evaluation metrics; - Experience setting up proactive monitoring and alerting systems to catch issues like model drift, performance degradation, or workflow failures. **Benefits** - Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps; - Competitive compensation; - A selection of exciting projects; - Flextime: Tailor your schedule for an optimal work-life balance.