Shape the testing strategy and framework at an organizational level as a Senior SDET, owning the foundation including AWS infrastructure, CI/CD pipelines, and Playwright test frameworks for the Rails platform.
Locations (2)
Canada
Vancouver, British Columbia, Canada
Compensation
The recruitment compensation range for this position is $87,600 - 109,500 - 131,400 (this range is base salary only).
Responsibilities
Lead the evolution of Thinkific’s test automation strategy by designing scalable and maintainable automation frameworks for web, API, integration, and component level testing
Develop advanced automation suites across front end, back end, services and integrations using modern tools such as Playwright, Cypress, Selenium or similar
Drive improvements to our CI/CD delivery pipeline by optimizing build efficiency, reliability and parallelization
Act as a technical mentor and coach for engineers and SDETs while elevating skills in test design, automation patterns and quality best practices
As a QA Automation Engineer, you will play an essential role in ensuring the quality, reliability, and performance of innovative digital products and applications. You will design and implement automated testing solutions that help development teams deliver seamless, high-quality user experiences.
Responsibilities
Design, develop, and maintain automated test scripts and frameworks to validate software functionality, performance, and reliability.
Create and execute automated test plans, test cases, and testing scenarios based on business requirements and technical specifications.
Perform functional, regression, integration, and end-to-end testing to ensure applications meet established quality standards.
Identify, document, track, and report software defects, working closely with development teams to support their timely resolution.
Collaborate with developers, product owners, business analysts, and other stakeholders to integrate testing activities throughout the software development lifecycle.
Seeking a detail-oriented and experienced Mid-Level QA Analyst to ensure the quality, reliability, and performance of digital solutions across multiple platforms, responsible for planning, designing, and executing both manual and automated testing strategies.
Responsibilities
Plan, design, develop, and execute manual and automated test cases to ensure software quality and reliability
Validate functional and non-functional requirements, identifying defects, inconsistencies, and potential performance issues
Perform functional testing across voice and text communication channels, ensuring accurate and consistent user experiences
Develop, implement, and maintain automated testing solutions using industry-standard methodologies, frameworks, and best practices
Execute API testing using Postman, validating endpoints, responses, integrations, and system behavior
Requirements
Bachelor's degree or postgraduate qualification in Information Technology, Computer Science, Software Engineering, or a related field
Ensure the quality, reliability, and performance of innovative financial technology solutions through comprehensive testing strategies.
Compensation
Annual base salary ranging from CAD 60,000 to CAD 75,000, depending on skills, experience, and role level. Exceptional candidates may be considered above the stated range.
Responsibilities
Review and analyze business requirements, technical documentation, and functional specifications to develop appropriate test strategies and comprehensive test cases.
Perform manual and automated testing, including functional, regression, integration, and user acceptance testing, to validate application functionality and overall system performance.
Conduct API and integration testing to verify RESTful APIs, third-party services, data exchanges, and interactions between different system components.
Execute database and backend testing using SQL to verify data integrity, transaction accuracy, and expected system behavior.
Identify, document, prioritize, and track software defects, providing clear reproduction steps and supporting information to help development teams investigate and resolve issues.
As a Quality Assurance Analyst, you will play a key role in ensuring the quality, reliability, and performance of a financial technology platform supporting credit card and payment solutions.
Compensation
Competitive base salary of CAD 60,000–75,000, depending on skills, experience, and role level.
Responsibilities
Review business and technical requirements and functional specifications to develop and execute comprehensive test cases.
Perform manual and automated functional, regression, integration, and user acceptance testing.
Conduct API and integration testing to validate RESTful APIs, third-party services, data exchanges, and system interactions.
Carry out database and backend testing using SQL to verify data integrity, transaction accuracy, and expected system behavior.
Identify, document, and track defects, providing clear reproduction steps and supporting information for investigation and resolution.
Requirements
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field
Define and drive quality engineering standards across a growing engineering organization, taking ownership of the company-wide quality vision, evolving existing testing practices, infrastructure, and AI-powered tools.
Compensation
Annual base salary ranging from $80,000 to $100,000 USD, depending on experience and qualifications.
Responsibilities
Own and continuously evolve the company-wide quality engineering roadmap
Define and improve testing approaches across the entire technology stack
Drive the adoption and evolution of AI-powered quality tools
Own and improve automated testing infrastructure, quality gates, required checks, end-to-end testing pipelines, visual regression testing, performance budgets, and mobile automation strategies
Determine which quality checks should block deployments and which can run asynchronously
Requirements
Nice to have: Claude Code
Nice to have: Model Context Protocol (MCP)-based workflows
As an AI Test Engineer II, you will play a key role in ensuring the quality, reliability, security, and performance of AI-powered applications and enterprise software systems.
Compensation
Competitive annual salary: $125,000–$150,000, depending on experience, skills, and qualifications.
Responsibilities
Design, develop, and maintain automated test suites covering API, user interface, security, and performance testing.
Develop end-to-end and integration tests using Playwright or comparable modern automation frameworks.
Create and maintain automated tests for REST and GraphQL services.
Leverage AI-powered coding and testing tools, such as Claude Code, GitHub Copilot, to generate, refactor, and scale automated tests.
Conduct security-focused testing covering authentication, authorization, input validation, and common OWASP vulnerabilities.
Requirements
Bachelor's degree in Computer Science, Engineering, or a related technical discipline, or equivalent professional experience
As an AI Software Development Engineer in Test, you will play a key role in redefining quality engineering for next-generation AI-powered applications and autonomous systems. You will go beyond traditional software testing to evaluate, validate, and improve large language models (LLMs), AI agents, copilots, chatbots, and intelligent workflows.
Responsibilities
Design, implement, and optimise testing strategies for AI-powered applications, copilots, chatbots, Retrieval-Augmented Generation (RAG) pipelines, and autonomous AI agents.
Develop AI evaluation (Evals) frameworks to assess hallucinations, groundedness, toxicity, bias, response quality, contextual relevance, prompt regression, consistency, and safety.
Build automated validation pipelines for LLM outputs using structured assertions, semantic scoring, embeddings, and evaluation metrics.
Create synthetic and benchmark datasets to support comprehensive AI testing scenarios.
Test multi-agent orchestration workflows, including agent memory, context retention, planning, and execution.
Requirements
Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, or a related discipline
Master's degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, or a related discipline
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