QA Engineer

LakeFusion is seeking a Quality Assurance (QA) Engineer to take ownership of testing and quality across our rapidly evolving Data & AI products. In this role, you will architect and implement comprehensive end-to-end testing strategies that ensure the reliability, accuracy, and performance of our LLM-powered features, entity resolution workflows, and data pipelines.You will play a hands-on role in building automation frameworks from the ground up, driving innovation in how complex AI/ML systems are tested, and ensuring quality at every stage of the development lifecycle. This includes validating everything from data ingestion and transformation to model inference, APIs, and user interfaces.As an early member of our QA function, you will also design and embed automation-driven QA processes within our CI/CD pipelines, leveraging GitHub Actions to enable rapid feedback and seamless product delivery. Working closely with Product Managers, Data Scientists, and Data/ML Engineers, you will collaborate within a lean, cross-functional team and act as a strong advocate for quality best practices.This is a highly self-directed role suited for a QA professional who thrives in a dynamic, fast-paced startup environment, where solving complex testing challenges and ensuring the integrity of AI-driven systems are central to success.

• Architect & Implement Testing Strategies: Develop and execute comprehensive, end-to-end quality assurance strategies and test plans specifically for LakeFusion's emerging Data & AI products, ensuring high reliability, accuracy, and performance of our LLM-powered features and data pipelines.
• Innovate AI/ML Testing: Independently devise and implement innovative testing approaches and methodologies tailored for complex AI/ML systems, including prompt engineering, RAG architectures, entity resolution, and data quality processes, with minimal guidance.
• Build Automation Frameworks: Lead the design, development, and deployment of early-stage, robust automation-driven quality assurance frameworks and processes from the ground up, capable of scaling with our product's rapid evolution.
• Integrate CI/CD: Implement and maintain continuous integration and continuous deployment (CI/CD) workflows for QA, specifically utilizing GitHub Actions, to ensure rapid feedback cycles and seamless product delivery.
• Full-Stack Quality Assurance: Conduct comprehensive testing across the full stack, from data ingestion and transformation pipelines, through AI/ML model inference, to API endpoints and user interfaces, ensuring end-to-end quality.
• Collaborate & Influence: Work effectively within a lean, cross-functional team including Product Managers, Data Scientists, and Data/ML Engineers, embedding quality throughout the development lifecycle and advocating for best practices.
• Problem Solve & Adapt: Tackle complex technical challenges with strong problem-solving abilities, thriving in the dynamic, rapidly-evolving environment of a startup organization.

• 5+ years of hands-on experience as a Quality Assurance Engineer, with a significant focus on data-intensive applications, AI/ML systems, or enterprise SaaS products.
• Proven expertise as a Full Stack QA engineer, capable of developing and implementing comprehensive testing strategies across backend, data, and frontend components.
• Demonstrated ability to design and implement innovative testing approaches for AI/ML systems, understanding the nuances of model performance, bias, data drift, and LLM-specific testing challenges.
• Extensive experience in developing and deploying automation-driven testing frameworks (e.g., Pytest, Selenium, Playwright, API testing tools).
• Proficiency in building and managing CI/CD pipelines utilizing GitHub Actions for automated testing and deployment.
• A highly self-directed professional with strong problem-solving abilities, comfortable owning ambiguous workstreams and delivering high-quality results independently.
• Solid understanding of software development methodologies (e.g., Agile, Scrum) and best practices for quality assurance in a fast-paced environment.
• Excellent communication and collaboration skills, with the ability to articulate technical issues clearly and work effectively with diverse teams.

• Hands-on experience with the Databricks platform (e.g., Delta Lake, MLflow, Databricks SQL Analytics).
• Familiarity with cloud platforms such as AWS & Azure for AI/ML deployments and data infrastructure.
• Experience with Master Data Management (MDM), Entity Resolution, or data quality concepts.
• Knowledge of Python for test automation and data validation.

LakeFusion is the modern Master Data Management (MDM) company. Global enterprises across industries ranging from retail to manufacturing and financial services  rely on the LakeFusion platform to unify, govern, and deliver trusted data entities such as customers, products, suppliers, and employees. Built natively on the Databricks Lakehouse, LakeFusion creates a single source of truth that powers analytics and AI. LakeFusion enables organizations worldwide to accelerate innovation with trusted and governed data.