Senior QA Automation Engineer – AI Applications

Autodesk•Toronto, ON

1d•CA$84,000 - CA$123,200

About The Position

We are seeking an experienced QA Automation Engineer to ensure the quality, reliability, and performance of AI-powered applications. The ideal candidate has expertise in automated testing and software quality engineering, with experience building scalable testing frameworks and leveraging AI-powered testing tools to improve test development, maintenance, and coverage. They combine deep QA automation expertise with practical experience using AI to enhance testing workflows. Experience testing AI/ML applications or validating machine learning models is an asset.

Requirements

Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
5+ years of professional experience in software quality assurance, test automation, or software engineering.
Strong programming skills in Python, with experience in test automation.
Hands-on experience using AI-powered testing tools or AI coding assistants to improve test automation, productivity, and quality.
Experience with CI/CD tools and processes.
Familiarity with popular CAD environments and tooling.
Proficient in automation and UAT test suites/frameworks.
Experience designing QA frameworks or platforms used by multiple teams.
Excellent problem-solving skills and attention to detail.
Strong communication and collaboration skills.
Understanding of software architecture and design patterns.
Ability to work in an Agile development environment.

Nice To Haves

Experience testing AI/ML applications or validating machine learning models.
Experience with data validation tooling (e.g., Great Expectations) or labeling workflows.
Familiarity with ML frameworks (e.g., PyTorch, TensorFlow).
Experience with data pipelines and orchestration tools (e.g., Airflow, Metaflow).
Knowledge of MLOps practices (e.g., model monitoring, drift detection, deployment validation).
Knowledge of ML evaluation methods, metrics, and benchmarking.
Passion for learning new technologies and improving existing systems.
Experience with cloud providers (e.g., AWS, Azure, Google Cloud Platform).
Experience testing AI/ML services in production environments.
Knowledge of experiment tracking tools (e.g., Comet, MLflow, Weights & Biases).

Responsibilities

Design and maintain automated test suites, evaluation scenarios, metrics, and test datasets for AI-powered features.
Automate QA workflows using Python and CI/CD (e.g., GitHub Actions, Jenkins), leveraging AI-powered testing tools to improve test development, maintenance, and coverage.
Create and maintain test harnesses for AI services, applications, and APIs.
Perform API testing for AI services and backend systems.
Define quality strategy and acceptance criteria for AI-powered applications across functional, API, integration, and AI/ML features.
Test AI/ML applications and machine learning models from a product and user perspective.
Evaluate AI/ML model outputs for correctness, consistency, and expected application behavior.
Define structured rubrics that translate qualitative findings into measurable evaluation gates.
Build quality gates for CI/CD and deployment pipelines, including automated regression and integration testing.
Mentor teams on QA automation best practices and consistent quality standards for AI-powered applications.
Contribute to multi-team projects and codebases, ensuring code quality and consistency.
Participate in code reviews and provide constructive feedback to peers.
Document and present findings and ideas across the company.