Job Description

This role will report onsite to our HQ in San Diego, CA.

Axos Bank is seeking a QA Automation Manager who serves as a strategic leader driving transformative change within the Centers of Excellence organization. This role owns the QA strategy, operating model, and delivery outcomes across manual and automated testing for integration, functional, regression, sanity, and performance validation—ensuring the highest quality standards for all software releases and adherence to internal SDLC processes. This leader accelerates adoption of AI-enabled Quality Engineering, including AI-assisted test design, automation generation, resilient and self-healing automation patterns, and modern evaluation and monitoring practices to increase delivery velocity while improving reliability, coverage, and confidence. The role partners closely with Engineering, DevOps, Product, and business stakeholders to embed quality deeply into modern CI/CD delivery practices and regulated environments.

Qualifications:

• Define and execute the QA strategy to expand the use of AI, automation and manual testing frameworks, including security/vulnerability testing and code coverage measures and improvements.
• Develop an executable QA roadmap with milestone deliverables, success metrics, and stakeholder alignment.
• Drive AI-assisted test generation, automation conversion, and resilient/self-healing automation to reduce maintenance and flakiness.
• Establish continuous quality evaluation, monitoring, and feedback loops, including quality gates and regression controls.
• Partner with Engineering and DevOps to embed quality into CI/CD pipelines and enforce release standards.
• Define and enforce quality standards, acceptance criteria, and release gating rules across teams.
• Lead end-to-end testing strategies across functional, performance, regression, web, mobile, and API layers.
• Oversee defect management, root-cause analysis, and preventative quality improvements.
• Analyze quality metrics, build actionable dashboards, and proactively address quality and delivery risks.
• Ensure compliance through regular quality audits and alignment with regulatory and risk management practices.
• Present quality insights, risks, and recommendations to senior leadership.
• Optimize testing processes and promote continuous improvement.
• Collaborate with product and business teams to incorporate customer feedback into quality outcomes.
• Lead, develop, and scale QA leadership and teams, building organizational capability in automation and AI-assisted Quality Engineering.

Requirements:

• Bachelor’s degree required
• 7+ years' of experience in Quality Assurance, including experience managing teams.
• 1+ years' of experience in financial services or related regulated industry.
• Strong understanding of SDLC and testing methodologies, including functional, performance, regression, automation tools, and CI/CD pipeline integration.
• Hands-on expertise building and maintaining test automation for web and mobile applications, APIs, and test data.
• Proven use of code coverage and quality analysis platforms such as SeaLights, SonarQube, or similar tools.
• Demonstrated success applying AI and GenAI to accelerate Quality Engineering, including AI-assisted test generation, AI-driven test data creation, and conversion of manual tests into automation.
• Track record of implementing resilient and self-healing automation patterns to reduce flaky tests and improve reliability.
• Working knowledge of LLMOps-style lifecycle practices for AI-enabled systems, including evaluation, validation, deployment gates, monitoring, and feedback loops.
• Experience embedding security and vulnerability testing into automated pipelines.
• Awareness of AI application security risks and testing approaches, including guardrails for prompt injection and sensitive data leakage.
• Understanding of AI risk management frameworks and governance concepts, such as NIST AI RMF, to support compliant adoption in regulated environments.

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