Senior Quality Engineer

• Define and track quality metrics (such as defect escape rate, automated coverage, and release risk score) for critical business domains, and share progress and trends with engineering and product teams.
• Design and drive a built-in quality strategy for your domain — such as shift-left testing, contract testing between services, or synthetic monitoring — aligned with business goals.
• Own ticketing pipeline and triage newly reported customer-facing issues, identify trends, and expedite critical issues to the relevant engineering teams as needed.
• Evaluate, pilot, and drive adoption of AI-assisted quality tools for use cases like test case generation, defect triage, and log analysis.
• Audit and expand automated test coverage across unit, integration, API, and end-to-end tiers — identifying gaps and prioritizing investments based on risk and usage data.
• Refine and automate production testing practices (e.g., canary releases, synthetic transactions, production error-rate dashboards) to catch escaped bugs quickly and drive fixes that prevent recurrence.
• Lead user acceptance and staging sign-off on major releases, coordinating directly with product and engineering teams to confirm readiness before launch.
• Run knowledge-sharing sessions, pairing, and test-plan reviews to raise the quality bar across engineering teams.
• Contribute to the team's evolving approach to asynchronous quality practices — helping move quality from a release gate to an ongoing, embedded discipline.
• Collaborate with external partners to represent K4B in the innovation and expansion of the application.

• 5+ years of experience understanding of quality metrics, their trade-offs, and how to combine them into a holistic view of product quality.
• Solid knowledge of CI/CD, version control, APIs, and how large-scale web applications work.
• Experience applying AI tools responsibly to test planning, issue triage, automation, or other quality workflows — equivalent experience with emerging tooling is equally welcome.
• A demonstrated ability to lead quality-focused projects and initiatives that span multiple teams or a broader engineering organization.
• Clear and effective communication skills, both in writing and in conversation, with a proactive approach to collaboration and a sense of ownership for team outcomes.
• Hands‑on experience with modern issue tracking software (e.g., Atlassian), and logging or observability platforms.
• A background in computer science or a related technical field — whether through a degree, a bootcamp, self-directed study, or equivalent hands‑on experience; all pathways are considered.
• Familiarity with release and off-cycle management processes is a plus, particularly if you are interested in participating in release rotation.

Demonstrates expertise in defining and tracking quality metrics, implementing AI-assisted quality tools, and leading cross-team quality initiatives. Proficient in CI/CD practices, automated testing strategies, and effective communication to enhance product quality.

• Quality Metrics Definition
• CI/CD Practices
• AI Tool Application
• Automated Testing Strategies
• Cross-Team Collaboration

• Quality Metrics
• Automated Testing
• Test Planning
• Issue Triage
• Defect Analysis
• API Knowledge
• Version Control
• Production Testing
• Risk Assessment
• Holistic Quality View

• Effective Communication
• Proactive Collaboration
• Ownership
• Knowledge Sharing
• Leadership

• Shift-Left Testing
• Contract Testing
• User Acceptance Testing
• Release Management
• Asynchronous Quality Practices

• Atlassian
• CI/CD Tools
• Logging Platforms
• Observability Tools
• Synthetic Monitoring