Senior Quality Engineer defining and executing quality strategies for AI-driven products. Collaborating on data engineering and application development for product reliability and user experience.
Responsibilities
Data Pipeline Validation: Test the integrity of data ingestion and transformation processes to ensure models are trained on high-quality datasets.
API & Model Testing: Conduct deep API testing using tools like APIDog to validate model responses, handling complex edge cases such as zero-value parameters or unauthorized access.
Generative Model Output Accuracy: Define and implement evaluation frameworks to measure the quality of generative AI outputs — including relevance, factual accuracy, coherence, and hallucination rate — using techniques such as LLM-as-a-judge, human-in-the-loop scoring, and automated benchmark suites.
AI Agent Response Validation: Design test strategies to assess the correctness and reliability of agentic AI responses, covering tool-call accuracy, multi-step reasoning integrity, goal completion rate, and graceful failure handling for out-of-scope or adversarial inputs.
Security Testing: Proactively identify vulnerabilities like request interception and price manipulation to safeguard the system including prompt injection and jailbreak attempts specific to generative AI surfaces.
UI Automation: Build and maintain scalable automation suites using low-code tools like mabl, aiming for high Mabl Test Coverage %.
AI Tooling Advocacy: Champion the use of AI assistants like Jira Rovo for requirement analysis and test case generation to increase team velocity.
Root Cause Analysis (RCA): Lead the RCA process for production bugs and developer-rejected tickets to continuously improve the "Definition of Done".
Requirements
Senior Experience: 8+ years of relevant work experience
Data Proficiency: Strong SQL skills and experience testing data-heavy applications or ML models.
Automation Mastery: Proficiency in automation tools (e.g., Selenium, mabl, Playwright)
Security Mindset: Understanding of OWASP principles and practical experience in security testing (request interception, label tracking).
Domain Knowledge: Experience in e-commerce and critical customer-flow analysis is highly preferred.
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