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San Francisco, California, United States
Hybrid
About the Role
Seeking a highly experienced QA professional who can operate comfortably across traditional QA, AI systems, and integration between the two worlds. This role is responsible for driving quality initiatives across AI driven workflows, mentoring QA team members, and partnering closely with Product and Engineering to ensure reliable, compliant, and scalable software releases.
Design and execute comprehensive test strategies covering end-to-end workflows, integrations, and event driven systems
Ensure accuracy and reliability of AI generated conversations, call summaries, and data capture across varied scenarios
Contribute to and maintain QA documentation, standards, and the organizational knowledge base
Partner with Product and Engineering to influence requirements, design decisions, and release readiness
Drive continuous improvement by identifying gaps in processes, tooling, and test coverage
Dig into technical problems and write clear, detailed, and repeatable defect reports
Conduct exploratory testing to evaluate robustness and functionality of products.
Work with QA engineers to increase automation coverage of features based on business priorities and risks
Demonstrate attention to detail and organization in all aspects of work
Bachelor’s degree in Computer Science or a related field, or equivalent practical experience
7+ years of experience in software quality assurance, including ownership of complex feature areas
Experience developing and executing test strategies for end to end workflows
Exposure to AI driven systems, conversational interfaces, or data driven automation preferred
Ability to quickly learn new products, technologies, and business domains
Experience validating AI or ML assisted features, including non deterministic outputs and regression risks
Advanced expertise in manual testing methodologies and test case design for complex systems
Strong experience testing APIs, webhooks, and third party integrations
Experience testing event driven architectures and downstream data delivery
Familiarity with compliance driven workflows, auditability, and data traceability
Strong analytical and problem solving skills with attention to detail
Excellent written and verbal communication skills, including clear defect documentation
Ability to influence development teams and advocate effectively for quality initiatives
