AI-Driven Data Quality Automation Engineer

Everpure; Prague (OK); On-site; USD 48,000 - 67,000; Full time

Benefits offered by this job

Flexible time off

Wellness resources

Team events

Job summary

Everpure is seeking an AI Quality Automation Engineer to join the Master Data Management (MDM) team in Prague. You will drive data reliability by building intelligent, automated testing systems for complex data pipelines.

You will collaborate with data engineers, software developers, and enterprise QA teams to deploy scalable, AI-driven test frameworks that ensure precision across enterprise data assets and accelerate release velocity from the core data engine.

Qualifications

• 3+ years of professional experience in quality software engineering or test automation.
• Experience with Prompt Engineering and AI-driven test automation strategies.
• Proficiency in Python or modern object-oriented programming to engineer modular test suites and validation pipelines.
• Hands-on experience building CI/CD deployment pipelines using GitHub Actions.

Responsibilities

• Design and execute automated test suites and AI evaluation frameworks to detect data anomalies and validate pipeline logic.
• Scale and optimize an end-to-end testing platform using generative AI models and agentic workflows.
• Automate CI/CD pipelines to ensure high stability and release velocity for MDM applications.
• Define automated quality gates and data precision metrics in collaboration with cross-functional teams.
• Enhance telemetry and observability by integrating automated monitoring into CI/CD pipelines.

Skills

Quality software engineering

AI & LLM integration

Problem-solving & collaboration

Location: Prague office

Tools

Python

GitHub Actions

CI/CD tooling

AI testing frameworks

Job description

Everpure is seeking an AI Quality Automation Engineer to join the Master Data Management (MDM) team in Prague. You will drive data reliability by building intelligent, automated testing systems for complex data pipelines.

You will collaborate with data engineers, software developers, and enterprise QA teams to deploy scalable, AI-driven test frameworks that ensure precision across enterprise data assets and accelerate release velocity from the core data engine.