Quality Engineer IV

About the role

The Quality Engineer IV plays a pivotal role in driving quality strategy and technical direction across teams and systems. This role is key in enterprise-level quality initiatives, influencing architecture decisions, and ensuring scalable, maintainable, and high-performing testing practices.

Responsibilities

• 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.
• Led 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.

Qualifications, Skills & Experience

• 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.
• 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.
• 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.

How will the ideal candidate use AI as an Efficiency Multiplier?

• 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.

Culture & Benefits

At Availity, we foster a collaborative and open culture where communication and engagement are central to our success. We are a remote-first company and require video participation during all virtual meetings to ensure security and protect sensitive information. Availity is committed to diversity, inclusion, and equal opportunity. We offer competitive compensation, a robust benefits package, and opportunities for professional growth and community involvement.