Senior Software Quality Engineer; Remote Austin, TX Remote

Location: Remote

Work anywhere in the US, must live in the US

We are growing! Join an Agile technology team of 40+ talented developers, test engineers, project managers, etc., who support a company of 150+ people with industry-leading web applications in areas of subscription-based continuing education, simulation and training, eCommerce, content management, and more.

A leader in online education, Continued is composed of passionate individuals dedicated to empowering professionals, enhancing careers, and strengthening teams. We are fast-paced, nimble, and laugh a lot. We all work from home offices in various locations across the country. We are dynamic, engaged, highly motivated, and highly skilled. We are passionate about our work and our professions and we’re looking for another team member to join our cause.

We are certified as a great workplace, ranked #35 in Fortune's 2025 Best Medium Workplaces, ranked #18 in Fortune's 2025 top 25 Small & Medium Workplaces for Women, and ranked #74 in Fortune’s 2024 Best Small & Medium Workplaces for Millennia ls by the independent analysts at Great Place to Work®. Learn more about us at

Though we are virtual and scattered across the country, we communicate frequently, have a tight-knit team, and support each other across roles and projects. We are driven by endless curiosity, a love of learning, and a desire to solve problems.

We are seeking a Senior Software Quality Engineer who will lead quality strategy in an AI-augmented API engineering environment. This role goes beyond traditional test automation — you will define quality intelligence frameworks, validate AI-powered features, and embed continuous quality practices across the SDLC.

You will partner with Engineering, Product, Data, and Tech Ops teams to ensure our systems are reliable, scalable, observable, and responsible.

• Define and drive AI-driven API risk-based testing strategies across distributed systems.
• Establish quality gates within CI/CD pipelines.
• Perform API tests with Graph
  
  QL within Apollo Studio.
• Lead test architecture decisions for microservices and AI-integrated platforms.
• Leverage AI tools (e.g., Claude, Cursor, Git Hub Copilot) to accelerate test creation and maintenance.
• Mentor and guide QA engineers on modern AI-driven quality engineering practices.
• Design self-healing and resilient automation frameworks.
• Validate AI-generated test artifacts for completeness and risk alignment.
• Leverage telemetry, logs, Honeycomb, and user behavior data to identify systemic risks and design synthetic monitoring and anomaly detection strategies.
• Track API error rates, latency, and SLA adherence.
• Build feedback loops between incidents and preventive improvements.
• Perform defect trend analysis and predictive risk modeling.
• Advocate for API design best practices, testability, observability, and reliability during architecture reviews and system design discussions.
• Embed AI-driven security and performance testing into the development lifecycle.
• Help build a culture where quality accelerates delivery.
• Research and evaluate emerging AI-powered testing tools and methodologies to enhance test generation, maintenance, and defect detection.
• Author pull requests for bug fixes where appropriate to help reduce developer cycle time and accelerate delivery.
• When needed, assist the web application testing team.

Self-management and time management are critical in this role. Without them, you will not be successful. Other requirements include:

• Bachelor's degree in Computer Science, Engineering, or a related field preferred
• Experience designing and building AI-driven API test automation frameworks from the ground up.
• Hands-on experience with Graph
  
  QL API testing, including schema validation, query/mutation testing, and working within or alongside Apollo Studio
• Experience integrating automated tests into CI/CD pipelines (e.g., Git Hub Actions, Circle
  
  CI)
• Mastery of AI-powered API testing tools and demonstrated ability to coach and share knowledge.
• Deep understanding of CI/CD, Dev Ops, and cloud-native architectures.
• Ability to read, debug, and write basic code —…