Quality Engineer IV

Availity is a leading healthcare engagement platform that delivers revenue cycle and related business solutions for healthcare professionals. The Quality Engineer IV is responsible for driving quality strategy and technical direction across teams and systems, ensuring quality is built into the development lifecycle while mentoring engineers and influencing architecture decisions.

Responsibilities:

• Assigned to a Scrum team, leads the definition and execution of test strategy to ensure comprehensive coverage aligned with product and architectural goals
• Drives quality outcomes within the Scrum team by identifying risks early, influencing design decisions, and ensuring testability and scalability of solutions
• Leads automation strategy within the team, including framework design, maintainability, and integration into CI/CD pipelines
• Identifies and mitigates systemic quality risks that extend beyond the immediate team, collaborating across teams when necessary
• Mentors and guides engineers within and outside the Scrum team on automation practices, test strategy, innovative approaches to AI and quality engineering standards
• Contributes to and promotes best practices for testing, automation, and quality engineering across teams and the broader organization
• Participates in and contributes to cross-team initiatives and discussions that impact quality strategy, tooling, and engineering practices

Requirements:

• Experience in an Agile/Scrum environment; we operate in 2-week sprints
• 8+ years of experience in software quality engineering, including leading testing efforts in complex, high-scale environments with an automation-first approach
• 6+ years of hands-on experience designing and evolving automation frameworks for UI, API, and integration testing, ensuring scalability, maintainability, and long-term sustainability
• Deep expertise in automation development using modern languages such as JavaScript, Python, or C#, with the ability to guide others in writing performant, maintainable, and reusable automation code
• Strong experience leveraging development tools and IDE ecosystems (VS Code, Eclipse, or similar), including extensions and integrations, to accelerate automation development, debugging, and analysis workflows
• Expert-level experience integrating high value automated testing into CI/CD pipelines, ensuring reliable and efficient validation in continuous delivery environments
• Expertise of cloud concepts (AWS, Azure including environments, deployments, and cloud-hosted architectures)
• Proven ability to troubleshoot and resolve complex automation and pipeline failures, including test flakiness, environment instability, and systemic issues
• Strong understanding of API automation, service virtualization, and test data management, with the ability to determine optimal test layering (API vs UI vs integration)
• Proven ability to lead and influence automation architecture decisions, improving system testability, scalability, and long-term reliability
• Demonstrated ability to mentor engineers in automation best practices, framework usage, and effective test design, elevating automation maturity across teams
• Strong understanding of underlying technologies supporting the applications under test, including APIs, distributed services, data systems, and cloud-based platforms
• Acts as an early adopter and champion of AI-enabled testing practices, proactively exploring new tools and approaches to improve quality engineering efficiency and effectiveness
• Designs, builds, and demonstrates AI-driven solutions that improve test strategy, automation development, defect analysis, and risk identification across the team and broader organization
• Leverages AI to proactively identify gaps in test coverage, uncover edge cases, and assess functional and non-functional risks across complex systems
• Applies AI to accelerate root cause analysis by synthesizing logs, test results, and system behaviors, enabling faster and more accurate decision-making
• Creates reusable AI-enabled tools, scripts, or workflows that improve team productivity and scalability of quality practices
• Mentors and trains engineers on effective and responsible AI usage, promoting best practices in prompting, validation, and integration into daily workflows
• Actively shares learnings, demos solutions, and drives adoption of AI capabilities across teams to elevate the overall effectiveness of the Quality organization
• Uses AI responsibly with strong human oversight, ensuring outputs are validated, accurate, and suitable for use in testing and release decision
• Healthcare industry and X12 EDI experience is a plus
• Experience with RedShift is a plus
• AWS experience is a plus