J&M GroupVerified Job Source

Sr. Software Quality Engineer – AI Acceleration / Global DevOps

Toronto, ON
On-site
Posted Oct 2, 2026
1 position

Opens an external site

Employment type: Full-time
Experience level: Senior · 5+ years
Apply by: Mar 29, 2027
Posting language: English
Working hours: 40 hours per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Develop and maintain scalable automated testing frameworks and quality strategies for DevOps tools, pipelines, and AI-enabled features. Integrate functional, API, integration, and AI quality checks into CI/CD workflows, track defects and quality trends, and communicate risks and release recommendations to stakeholders.

Job details

We are looking for a seasoned AI-first Senior Quality Engineer who is empowered to help the DevOps enablement team deliver the highest level of quality and is responsible for ensuring the team lives quality values and principles. The DevOps team is responsible for providing pipelines, metrics, and tools for use by application development teams. The incumbent will actively participate in gathering quality criteria from the user community, developing a backlog of items, prioritizing them with the teams, and delivering them continually. What You Will Do Partner with DevOps, Development, Product, and QE teams to design and execute exploratory, automated, and AI-focused tests that ensure product quality. Define quality strategies, test plans, test cases, and test data for functional, integration, system, regression, API, database, and acceptance testing. Design, develop, and maintain scalable test automation frameworks using Java, Python, or Groovy. Build automated tests for AI-enabled features, including prompt behavior, response accuracy, hallucination risks, safety, reliability, latency, and regression coverage. Validate AI integrations, APIs, microservices, data pipelines, model interactions, and third-party services. Establish testing approaches for both deterministic and non-deterministic AI behavior, including evaluation datasets, expected behavior, quality thresholds, and repeatability. Integrate automated testing and AI quality checks into CI/CD pipelines in partnership with DevOps teams. Use tools and frameworks such as Selenium, Cucumber/Gherkin, Playwright, RestAssured, JUnit, TestNG, ReadyAPI, and JMeter. Identify, document, prioritize, and track defects through resolution. Analyze test coverage, quality trends, AI evaluation results, and production feedback to identify gaps and drive continuous improvement. Collaborate with cross-functional Agile teams to deliver reliable, secure, and user-focused product features. Communicate test results, risks, quality metrics, and release recommendations clearly to technical and non-technical stakeholders. Essential Skills 5 years of relevant experience in Quality Engineering, Quality Assurance, test automation, or software development. 5 years of programming experience with Java, Python, Groovy, or a comparable language. 5 years of experience building and maintaining test automation frameworks. Hands-on experience with Selenium, Cucumber/Gherkin, Playwright, RestAssured, or similar automation technologies. Experience testing functional and non-functional requirements, APIs, integrations, databases, microservices, and regression suites. Experience with testing frameworks and tools such as JUnit, TestNG, qTest, ReadyAPI, and JMeter. Understanding of TDD, ATDD, BDD, continuous testing, and risk-based testing practices. Experience testing AI or machine learning-powered applications, APIs, conversational systems, or generative AI features. Understanding of AI quality concepts such as prompt evaluation, grounding, accuracy, relevance, toxicity, bias, hallucination detection, and response consistency. Ability to create effective test data and evaluation datasets for AI-driven functionality. Strong analytical, problem-solving, communication, and technical documentation skills. Ability to work effectively in a fast-paced, cross-functional Agile environment. Nice to Have Experience with AI evaluation frameworks, LLM testing, prompt engineering, retrieval-augmented generation, embeddings, or model observability. Experience with Git, Bitbucket, Jenkins, CI/CD pipelines, Artifactory, SonarQube, Jira, Confluence, AWS, Kubernetes, Maven, or Gradle. Experience testing cloud-native applications and distributed microservice architectures. Experience with security, performance, accessibility, or reliability testing. Experience developing automation scripts and reusable testing utilities. Experience with Tableau or other relevant tools.

What you’ll do

Requirements

Requires at least five years of relevant quality engineering, test automation, or software development experience, including five years programming and building automation frameworks. Candidates should have experience testing APIs, integrations, and AI-powered applications, understand AI quality evaluation and testing methodologies, and be effective communicators in cross-functional Agile teams.