QA Engineer

Lakefusion; United States; Remote; USD 90,000 - 130,000; Full time

Job summary

Lakefusion is seeking a hands-on QA engineer to own end-to-end quality for evolving data and AI products, including LLM-powered features. This role suits a self-directed tester who thrives in a fast-paced environment and aims to build automation frameworks from the ground up while partnering with product, data science, and engineering teams.

You will architect QA strategies, build automation from scratch to validate data pipelines, APIs, and UIs, and embed tests into CI/CD pipelines for rapid

Qualifications

• Experience architecting end-to-end testing strategies for AI/ML or data products.
• Track record building automation frameworks and integrating them into CI/CD pipelines.
• Familiarity with validating LLM-powered features and handling non-deterministic outputs.
• Comfort working across data, API, and UI layers.
• Experience collaborating inside lean, cross-functional product teams.
• Self-directed working style suited to fast-paced environments.
• Python knowledge for test automation and data validation.

Responsibilities

• Architect and execute end-to-end QA strategies tailored to AI/ML systems.
• Build automation frameworks from scratch to validate data ingestion, transformation, model inference, APIs, and UI.
• Design and embed automated QA processes into CI/CD pipelines for rapid feedback and reliable delivery.
• Develop innovative testing approaches for complex AI/ML behavior, including LLM output validation.
• Collaborate with product managers, data scientists, and engineers to advocate for quality best practices.
• Validate entity resolution workflows and data quality outcomes across pipelines.

Skills

End-to-end QA for AI/ML

Automation framework development

CI/CD integration

Python for test automation

LLM output validation

Cross-functional collaboration

Self-directed work style

Tools

Automation frameworks

CI/CD tooling

Python tooling

API testing

UI testing

Delta Lake

MLflow

AWS

Azure

Job description

Role overview

A hands-on QA role responsible for end-to-end quality across evolving data and AI products, including LLM-powered features, entity resolution workflows, and data pipelines. The position is suited for a self-directed tester who thrives in a fast-paced environment and wants to build automation frameworks from the ground up while partnering closely with product, data science, and engineering teams.

Responsibilities

• Architect and execute end-to-end QA strategies and test plans tailored to AI/ML systems.
• Build automation frameworks from scratch to validate data ingestion, transformation, model inference, APIs, and user interfaces.
• Design and embed automated QA processes into CI/CD pipelines for rapid feedback and reliable delivery.
• Develop innovative testing approaches for complex AI/ML behavior, including LLM output validation.
• Collaborate with product managers, data scientists, and engineers to advocate for quality best practices.
• Validate entity resolution workflows and data quality outcomes across pipelines.

Requirements

• Experience architecting comprehensive end-to-end testing strategies for AI/ML or data products.
• Track record building automation frameworks and integrating them into CI/CD pipelines.
• Familiarity with validating LLM-powered features and handling non-deterministic outputs.
• Comfort working across data, API, and UI layers.
• Experience collaborating inside lean, cross-functional product teams.
• Self-directed working style suited to fast-paced environments.
• Python knowledge for test automation and data validation.

Nice to have

• Familiarity with lakehouse platforms such as Delta Lake, MLflow, or related tooling.
• Cloud platform experience with AWS or Azure for AI/ML deployments and data infrastructure.
• Background in Master Data Management, entity resolution, or data quality concepts.