Join an innovative technology team developing AI-powered healthcare solutions that combine behavioral science, data science, and machine learning to improve patient engagement and health outcomes. As the Lead, Software Quality Assurance, you will define and drive quality engineering strategy across a cloud-native platform, user interfaces, APIs, and customer integrations. You will champion a shift-left approach, embedding automated testing, risk-based validation, and quality controls throughout the software development lifecycle. Working closely with engineering, product, cloud infrastructure, and customer operations teams, you will help ensure that releases are reliable, secure, scalable, and audit-ready in a regulated healthcare environment. You will also mentor QA engineers, establish shared testing standards, and continuously improve automation frameworks and delivery processes. This remote opportunity offers the chance to influence engineering excellence while helping deliver dependable technology that supports meaningful improvements in healthcare.
- Lead quality assurance strategy: Define, implement, and maintain comprehensive testing strategies across platform services, APIs, web interfaces, event-driven workflows, and data pipelines.
- Drive test automation: Build and evolve automated testing frameworks covering unit, integration, contract, regression, and end-to-end testing, complemented by risk-based manual testing where automation is not practical.
- Establish quality gates: Define and maintain CI/CD quality controls, including coverage thresholds, contract test validation, critical-path end-to-end testing, and security scanning where applicable.
- Embed quality early in development: Partner with engineers and product owners to review requirements, acceptance criteria, application logic, APIs, data models, event contracts, and user workflows to improve testability from the design stage.
- Validate performance and reliability: Ensure appropriate testing of system performance, resilience, timeouts, retries, idempotency, failure scenarios, and other operational risks.
- Strengthen event-driven testing practices: Establish standards for Kafka-based and similar messaging systems, including schema validation, backward compatibility, message replay, ordering assumptions, and failure handling.
- Improve observability and release readiness: Collaborate with cloud and site reliability engineering teams to validate logging, metrics, tracing, operational dashboards, and production readiness before releases.
- Maintain automation quality: Establish standards for reliable, maintainable automated tests, reduce flaky test behavior, assign clear ownership, and ensure timely remediation of broken tests.
- Mentor and develop QA talent: Coach QA engineers, conduct code and test reviews, facilitate knowledge sharing, and develop playbooks, documentation, training, and cross-team testing practices.
- Support product development: Collaborate with product owners and developers during backlog refinement, sprint planning, requirements clarification, and other Agile ceremonies to ensure features are testable and meet acceptance criteria.
- Drive continuous improvement: Evaluate new testing tools and techniques, improve test data management, support local and ephemeral test environments, and identify opportunities to accelerate delivery without compromising quality.
- Support production operations: Participate in release support, incident triage, defect investigation, and root cause analysis alongside engineering, cloud infrastructure, and customer operations teams.
- Reduce recurring defects: Monitor escaped defect trends and implement corrective actions through improved tests, quality gates, and development processes.
- Document and standardize processes: Maintain clear QA procedures, testing guidelines, and engineering quality standards that support consistency across teams and releases.
Requirements:
- Professional experience: Five to seven or more years of relevant experience in software quality assurance, quality engineering, test automation, or a related technical discipline.
- Education: A bachelor's degree in a related field is preferred.
- API and service testing: Demonstrated experience automating tests for APIs and backend services, using tools such as JUnit, TestNG, or PyTest.
- UI automation: Practical experience with browser and user interface automation tools such as Cypress, Playwright, or Jasmine, where applicable.
- Performance testing: Familiarity with performance and load testing tools such as Gatling, k6, or JMeter.
- Contract testing: Experience with contract testing frameworks such as Pact or equivalent tools.
- CI/CD and version control: Strong understanding of continuous integration and delivery pipelines, quality gates, source control, and Git-based development workflows.
- Observability: Familiarity with monitoring, logging, metrics, and distributed tracing concepts, including tools such as Datadog and OpenTelemetry.
- Cloud and infrastructure: Experience working with cloud platforms such as AWS or Azure, with familiarity with Kubernetes and cloud-native application architectures.
- Programming and scripting: Proficiency in one or more relevant programming or scripting languages, such as Java, TypeScript, Groovy, or Python.
- Data and messaging technologies: Experience working with SQL databases and event-driven systems, particularly Kafka or comparable messaging technologies.
- Agile methodologies: Familiarity with Agile development practices and frameworks, including Scrum, Extreme Programming (XP), or SAFe.
- Leadership and mentoring: Demonstrated ability to guide QA engineers, share technical knowledge, establish best practices, and influence quality standards across multiple engineering teams.
- Risk-based decision-making: Strong judgment in assessing testing priorities, evaluating release risks, and balancing quality, reliability, and delivery speed.
- Process improvement: A proactive mindset and the ability to work through ambiguity, improve systems incrementally, and introduce practical solutions without waiting for perfect processes.
- Communication and collaboration: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
- Organization and adaptability: Strong time management, prioritization, problem-solving, and organizational skills in a dynamic, cross-functional environment.
- Work authorization: Must be authorized to work in the United States without requiring employer-sponsored work authorization.
- Onboarding requirement: Must be able to attend an initial one-week onsite onboarding period at an office in Tennessee. Travel expenses for this required visit are covered by the employer.
Benefits:
- Competitive salary: Annual salary ranging from $130,000 to $150,000 USD.
- Remote work flexibility: Work remotely within the United States, with a hybrid option available for employees located in Tennessee.
- Healthcare coverage: Medical insurance with access to a Health Savings Account (HSA), plus dental and vision coverage.
- Disability protection: Company-paid short-term and long-term disability insurance.
- Life insurance: Company-paid life insurance and accidental death and dismemberment (AD&D) coverage.
- Retirement savings: A 401(k) plan with employer matching.
- Paid holidays: Ten paid holidays, along with quarterly company closure dates and an additional holiday-week company closure.
- Flexible time off: A flexible paid time off policy to support personal needs and work-life balance.
- Paid parental leave: Six weeks of paid parental leave to support employees and their growing families.
- Travel-covered onboarding: Travel expenses covered for the required first week of onsite onboarding at a Tennessee office.
- Meaningful impact: The opportunity to contribute to AI-powered healthcare solutions designed to improve preventive care, chronic disease management, patient engagement, and overall well-being.
- Technical leadership opportunities: The ability to shape quality engineering practices, mentor team members, and influence reliability and testing standards across a cloud-native platform.
