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Remote mid-level generalist QA with broad full-stack requirements increases applicant density.
Specialized AI/ML and data-pipeline testing knowledge reduces transferable fit across industries.
Requires 5+ years, AI/ML testing expertise and specific automation/CI tools, making filters stringent.
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Own and architect end-to-end testing strategies for LakeFusion's Data & AI products focusing on LLM-powered features, entity resolution workflows, and data pipelines.
Build and deploy automation-driven QA frameworks from scratch integrated with CI/CD pipelines using GitHub Actions to enable rapid feedback and seamless delivery.
Collaborate with cross-functional teams including Product Managers, Data Scientists, and Data/ML Engineers to embed quality best practices throughout the development lifecycle.
5+ years of hands-on experience as a Quality Assurance Engineer with focus on data-intensive applications, AI/ML systems, or enterprise SaaS products.
Proven expertise in full-stack QA including backend, data, and frontend testing strategies.
Experience developing and deploying automation testing frameworks (e.g., Pytest, Selenium, Playwright) and managing CI/CD pipelines using GitHub Actions.
Work Experience Required: 5+ years as a Quality Assurance Engineer.
Experienced in testing complex AI/ML systems with understanding of model performance, bias, and LLM-specific challenges.
Skilled in building automation frameworks for scalable QA in a fast-evolving startup or product environment.
Able to independently own ambiguous workstreams with strong problem-solving skills and collaborate effectively in lean, cross-functional teams.