Ai Quality Assurance Automation Engineer (Permanent) - Wellington

OverviewAI Quality Assurance Automation Engineer (Permanent) – Wellington.

Join a Digital Engineering team delivering innovative AI-driven software solutions.

You will work on cutting-edge projects, collaborating with cross-functional teams to design, develop, and deploy AI models that address complex business challenges.

This role requires a strong software background and a passion for AI.ResponsibilitiesAI QA Solutions Development : Design, develop, and implement advanced AI-powered QA automation solutions for testing AI-based applications, models, and systems.

Identify performance bottlenecks, inconsistencies, and model biases.Test Automation & Frameworks : Build and maintain automated test frameworks for AI systems using tools such as Playwright, Appium, Pytest, or custom AI testing tools.

Ensure scalability, reusability, and adherence to best practices.

Senior automation coding skills in Python, TypeScript, Java, or C#.

AI Model Testing : Perform functional and non-functional testing of AI models to assess accuracy, bias, scalability, and robustness.

Conduct regression testing and validate behavior across different scenarios.Adopt AI Innovations : Stay up to date with AI advancements and adopt emerging AI technologies to improve QA processes (e.g., GPT models, neural networks, reinforcement learning).

Cloud and On-Premise AI Services : Test and validate AI solutions hosted on cloud platforms (AWS, Azure, Google Cloud) and on-premise services; ensure optimal performance across environments.Cross-functional Collaboration : Work with AI developers, data scientists, and product teams to identify testing requirements, troubleshoot issues, and provide QA insights on solution design.Continuous Improvement : Implement and continuously improve testing methodologies for AI systems; drive automation efficiency and align with rapid AI development cycles.Pipeline Development : Describe and demonstrate the value of test automation pipelines for AI solutions using PaaS (e.g., Azure DevOps, GitHub Actions).

Quality Metrics & Reporting : Establish quality metrics, track progress, and report on testing outcomes, issues, and resolutions; maintain clear documentation.Communication : Communicate abstract concepts and value points clearly to stakeholders, both in writing and verbally.Skills & QualificationsExperience : 4–5 years in test automation with a focus on AI / ML applications; proven ability to build automated frameworks.Technical Skills : Proficient in Python, C#, Java, or TypeScript with strong Python experience; hands-on with Selenium, Appium, Pytest, or similar frameworks.Cloud & On-Premise AI : Experience with cloud AI services (AWS AI / ML, Azure Cognitive Services, Google Cloud AI) and on-premise AI solutions.Version Control & CI / CD : Knowledge of Git and CI / CD pipelines for automated testing.AI / ML Knowledge : Basic understanding of AI / ML concepts, data preprocessing, model training, evaluation metrics, and model fairness; experience testing AI systems (model validation and performance).

Analytical & Problem-Solving : Strong analytical skills to assess AI performance, debug issues, and improve test coverage.Learning & Adaptability : Ability to stay current with AI trends and quickly adopt new tools and methodologies.Collaboration & Communication : Excellent teamwork and the ability to explain technical concepts to technical and non-technical stakeholders.Preferred QualificationsExperience with on-premise AI services and hybrid deployments.Familiarity with AI ethics, fairness, and bias testing methodologies.Experience with test-driven development (TDD) or behavior-driven development (BDD) in AI projects.Why join usBe part of a dynamic, forward-thinking team pushing the boundaries of AI technology.Environment that encourages innovation and continuous learning.Opportunity to lead in AI QA and directly impact the quality of AI products.Competitive salary and benefits package.

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