Senior Software Quality Engineer

About Myant:

At Myant, our mission is to help people Live Younger, Longer by transforming healthcare from episodic, reactive care to proactive, preventive health management. Through our pioneering connected textiles and continuous monitoring technology, we bridge the gap between individuals, their families, and healthcare providers—creating a world where quality healthcare is more accessible, personalized, and preventative.

Powered by extensive, multidisciplinary R&D, Myant combines expertise in textile science and computing, biometrics, AI, and clinical research to develop technologies that seamlessly integrate into everyday life. Our innovation engine continuously expands the platform’s capabilities, addressing cardiovascular health, stress management, sleep optimization, and more.

With global ambitions, Myant is building a worldwide presence—collaborating with healthcare systems, clinics, researchers, and partners to set a new standard in connected health. Our goal is not just to improve care, but to fundamentally redefine the relationship people have with their health, shifting the focus from sick care to lifelong wellness.

By combining cutting-edge biometric sensing, AI-powered insights, and evidence-based behavioral coaching, Myant helps individuals and healthcare teams work together to prevent disease, optimize wellness, and unlock healthier, longer lives.

Role Overview:

We are hiring a Senior Software Quality Engineer to shape how Myant tests health software in an AI-augmented world. Our software is used by patients and healthcare professionals and handles sensitive health information. Here, quality means patient safety and privacy, not simply whether the software works.

You will own the quality strategy for the platform end to end, from defining test scope and depth to establishing the criteria every release must meet. You will remain hands-on with testing and automation while using AI to accelerate the work without lowering the quality standard.

In health software, a defect can mean a patient receives an incorrect risk result or a user gains access to a record they should not see. You will approach failures through that lens, prioritizing risks to patient safety and privacy over cosmetic issues.

This is not a traditional manual QA or script-maintenance role. We are looking for an engineering-minded quality leader who thinks systematically about correctness, regression prevention, observability, and long-term platform reliability, and who treats AI as an integral part of the engineering toolkit rather than a novelty.

Job Responsibilities:

Quality Strategy and Release Readiness

• Own and evolve the platform’s test strategy using a risk-based approach, prioritizing areas that could impact patient safety, privacy, or the protection of personal health information (PHI).
• Define clear release exit criteria and provide evidence-based recommendations on release readiness.
• Engage in requirements and refinement discussions to ensure user stories and acceptance criteria are clear, complete, and testable before development begins.
• Communicate quality risks, findings, and recommendations clearly to engineering, product, and clinical stakeholders.

Privacy, Security, and Clinical Safety

• Own the testing approach for access control, data privacy, and security, ensuring users can access only the information and functionality appropriate to their role.
• Partner with clinical and domain experts to validate the accuracy of health-related functionality and ensure invalid, incomplete, or unexpected data is handled safely.
• Integrate privacy, consent, and security requirements into testing from the outset rather than treating them as end-of-cycle checks.

AI-Augmented Testing

• Use AI assistants to accelerate test design, test data generation, automation, analysis, and other quality engineering activities, while reviewing and validating AI-generated output.
• Build reusable AI-assisted workflows that integrate with development and testing tools to improve efficiency and coverage.
• Apply AI to areas such as test failure analysis, flaky test investigation, defect analysis, and identifying patterns across test and quality data.
• Evaluate emerging AI testing capabilities and recommend adoption based on clear quality, reliability, security, and maintainability criteria.
• Establish appropriate guardrails for AI-assisted testing, including human review, data privacy, and traceability to requirements.

Testing AI-Powered Features

• Design test and evaluation approaches for AI-powered features, considering areas such as accuracy, safety, privacy, data scoping, non-deterministic behaviour, security, model changes, and other AI-specific risks.
• Build evaluation datasets and automated checks to monitor AI feature quality and detect regressions over time.

Automation and Quality Engineering

• Build and maintain reliable automation across web, mobile, and API layers, integrating automated tests into CI/CD.
• Continuously improve test coverage, execution speed, reliability, and maintainability, including investigating and reducing flaky tests.
• Develop and maintain synthetic test data and controlled test environments that support repeatable and reliable testing without using real patient data.
• Contribute to testing across accessibility, compatibility, performance, and security as appropriate to the product and risk.

Defect Management and Mentoring

• Create clear, reproducible defect reports with appropriate evidence and verify fixes across relevant builds and environments.
• Mentor developers and QA engineers on effective test design, quality engineering practices, automation, and responsible use of AI tools.

Qualifications:

• 6+ years of experience in software quality engineering, test automation, or a related engineering discipline, with at least 2 years in a senior or technical leadership role.
• Strong JavaScript or TypeScript skills, with hands-on experience building and maintaining modern test automation using Playwright, Cypress, Selenium, or similar tools.
• Experience testing REST APIs, authentication, authorization, and secure application workflows.
• Proven experience testing role-based access, permissions, and data isolation in applications with multiple user types or organizations.
• Hands-on experience testing mobile applications on iOS or Android, including functional, integration, and compatibility testing.
• Strong test design skills, including risk-based testing, boundary and negative testing, equivalence partitioning, and exploratory testing.
• Strong debugging and root-cause analysis skills, with the ability to investigate failures across application, API, data, and integration layers.
• Experience integrating automated tests into CI/CD pipelines and using automation as part of the software development lifecycle.
• Practical, hands-on experience using AI coding and testing tools to improve productivity, coverage, and quality, with the judgment to identify and correct their limitations.
• Ability to design effective prompts and critically review AI-generated code, tests, and analysis for gaps, incorrect assumptions, and false confidence.
• Comfortable working in Agile teams and collaborating with product, engineering, and domain experts to clarify requirements and define testable acceptance criteria.
• Strong written and verbal communication skills, with the ability to explain technical issues and quality risks clearly to engineers, clinicians, product teams, and leadership.

Nice to have

• Experience working in healthcare, medical devices, financial services, or another regulated domain, with familiarity with relevant privacy, security, or software lifecycle requirements.
• Experience testing integrations involving healthcare standards such as FHIR or HL7, electronic medical records, connected devices, payments, or other external systems.
• Experience with accessibility testing, including screen readers and automated accessibility tools.
• Familiarity with application and API security principles, including OWASP guidance and security considerations for AI-powered features.
• Familiarity with LLM APIs, Agent Skills, the Model Context Protocol (MCP), or agent-based AI frameworks.
• Experience evaluating or using AI-assisted testing capabilities such as visual testing, self-healing automation, or autonomous test agents.
• ISTQB or another relevant software testing or quality engineering certification.

What We Offer:

• A unique opportunity to shape the future of connected healthcare
• Competitive salary and comprehensive benefits
• A collaborative, fast-paced environment where innovation and impact go hand-in-hand
• Opportunities for professional growth in a mission-driven company poised for global expansion
• Exposure working in one of the most innovative and forward-thinking tech company