Middle General QA

Що робити

Define and own the evaluation framework for AI features, including transcription accuracy, summary quality and needs categorization metrics
Validate real-time Japanese speech-to-text in live consultation sessions, covering streaming stability, speaker separation and handling of background noise
Build a ground truth data set together with the client domain experts and use it to score AI-generated consultation summaries and identified needs
Verify relevance of support service recommendations returned by knowledge base search, including location-based results and map display
Test the asynchronous processing pipeline (API Gateway, SQS, Lambda), confirming correct retries, error handling and dead letter queue behaviour

Possessing 3+ years of dedicated professional experience in quality assurance and automation engineering, demonstrating a strong track record of successful project contributions.
Demonstrated advanced proficiency in Quality Assurance methodologies and practices, ensuring high standards of software reliability and performance.
Possessing intermediate hands-on experience in QA Automation, including the design, development, and maintenance of automated test suites for web applications and REST APIs.
Strong working knowledge and intermediate-level experience with Python programming for scripting, test automation, and data analysis.
A foundational understanding and beginner-level exposure to Artificial Intelligence concepts, including LLM output evaluation, with an eagerness to explore its applications in QA.