QA Analyst

TL;DR

QA Analyst (Healthcare AI): Leading testing strategy and execution across functional, integration, and end-to-end systems for a healthcare CX platform with an accent on comprehensive test coverage, automation frameworks, and defect prevention. Focus on developing test plans, executing manual and automated tests, analyzing results, and collaborating with engineering teams to ensure release quality.

Location: Toronto, Ontario. Canada applicants only. Hybrid: in-office collaboration Monday through Thursday for Toronto-area employees (within 65 km of downtown HQ), with 10 or 20 flexible remote days per quarter.

Salary: $75,000–$90,000 CAD

Company

Leading AI-powered healthcare consumer experience platform reaching 63 million people worldwide, used by major payers, providers, and health partners.

What you will do

• Serve as primary tester on implementation projects, developing and maintaining test plans and cases based on requirements.
• Create and execute functional, integration, and E2E test cases to validate business systems and ensure high quality standards.
• Conduct peer reviews of test cases, review automated test results, and add functionality to automation frameworks.
• Identify, document, prioritize defects using Jira, and collaborate with engineers to track progress and mitigate risks.
• Comply with information security policies and secure coding practices.

Requirements

• Canada applicants only
• Bachelor's degree in Computer Science, Engineering, or related field.
• 5+ years in Quality Assurance with ability to write test plans, cases, and follow processes.
• Expertise in manual testing: functional, integration, E2E, and regression.
• Experience running test automation and reviewing results; ability to understand business requirements and develop comprehensive test scenarios.
• Demonstrated experience using AI tools responsibly in workflows; curiosity for new technologies.

Nice to have

• Experience in healthcare or regulated industries.

Culture & Benefits

• AI-native organization: expected to leverage AI for productivity, problem-solving, and workflows across all levels.
• Hybrid work model with in-office collaboration Mon-Thu and flexible remote days for focus time.
• Commitment to equal opportunity, diversity, and accommodations during recruitment.

Hiring process

• Confirmation email after application; recruiter reviews and reaches out if aligned.
• Team-specific interview process shared by recruiter; reference and background checks prior to offer.
• AI may assist in screening; transparency on process.