Sr. Quality Assurance Manager

The Lifetime Value Co.•,

1d•Remote

About The Position

The Lifetime Value Co. is looking for a Sr. QA Manager to join our Quality Assurance team. In this remote role, you will lead a team of QA Analysts responsible for delivering high-quality software while continuously improving the efficiency, speed, and effectiveness of quality assurance through automation and AI. As a Sr. QA Manager, you will be responsible for building a high-performing team that embraces modern testing practices, leverages AI to eliminate repetitive work, and continuously improves testing quality and delivery performance. You will work closely with Engineering and Product teams to ensure quality is built into every stage of the software development lifecycle. We are looking for a leader who combines strong people leadership with technical excellence, embraces AI as a daily productivity tool, and continuously challenges traditional QA practices to maximize business impact.

Requirements

Experience leading and developing high-performing QA teams.
Strong coaching and mentoring skills with a passion for helping others grow.
Ability to foster accountability, ownership, and continuous improvement.
Strong proficiency using AI tools to improve software testing, productivity, documentation, analysis, and engineering workflows.
Demonstrated ability to coach others in effectively leveraging AI while maintaining engineering quality.
Strong understanding of prompt engineering, AI-assisted software development, and practical applications of generative AI within QA.
Curiosity to continuously evaluate emerging AI technologies and integrate them where they provide measurable value.
Strong understanding of software testing methodologies, SDLC, Agile practices, and modern QA principles.
Experience with manual and automated testing across web and mobile applications.
Experience working with automation frameworks and CI/CD pipelines.
Familiarity with API testing, test management platforms, and defect tracking systems.
Strong organizational and prioritization skills.
Ability to manage multiple initiatives simultaneously.
Data-driven decision making with strong analytical thinking.
Comfortable working in a fast-paced environment with changing priorities.
Excellent verbal and written communication skills.
Strong cross-functional collaboration abilities.
Ability to communicate quality risks and technical concepts clearly to both technical and non-technical stakeholders.
High ownership and accountability.
Strong critical thinking and problem-solving skills.
Growth mindset and continuous learner.
Passion for innovation and improving how teams deliver quality.
Bachelor’s degree in Systems Engineering or a related field.
7-10 years of experience in Software Quality Assurance.
5+ years leading a team of QA Engineers or QA Analysts.
Proven experience with manual and automated testing across web and/or mobile applications.
Demonstrated proficiency using AI tools (such as ChatGPT, Claude, Cursor, GitHub Copilot, or equivalent) to improve engineering productivity and software quality.
Experience integrating automation into CI/CD pipelines.
Strong understanding of Agile software development.
Experience with modern test management and defect tracking platforms.
English — B2+ Advanced.

Responsibilities

Lead, mentor, and develop a team of QA Analysts through coaching, regular feedback, and career development.
Foster a high-performance culture centered on ownership, accountability, collaboration, and continuous learning.
Help team members grow their technical, automation, and AI capabilities.
Establish high expectations for quality, execution, and professional growth.
Own the successful execution of testing activities across multiple products and initiatives.
Ensure appropriate test coverage through effective test planning, exploratory testing, regression testing, and risk-based testing.
Drive quality throughout the software development lifecycle by partnering closely with Engineering and Product teams.
Ensure releases meet established quality standards before production deployment.
Champion the adoption of AI across the QA team to improve productivity, test quality, and delivery speed.
Coach QA Analysts on effectively using AI tools to accelerate test design, exploratory testing, defect analysis, root cause investigation, documentation, and test automation.
Continuously evaluate emerging AI capabilities and identify opportunities to improve QA workflows.
Ensure AI-generated outputs are validated through critical thinking and engineering judgment.
Promote responsible AI usage while protecting sensitive information and maintaining quality standards.
Expand automated regression coverage by identifying the highest-value automation opportunities.
Partner with Engineering teams to improve CI/CD testing practices.
Reduce repetitive manual testing through automation and AI-assisted workflows.
Continuously improve testing processes to increase efficiency, consistency, and release confidence.
Plan and coordinate QA activities across multiple projects.
Balance priorities, timelines, and team capacity to meet delivery commitments.
Identify risks early and proactively remove blockers.
Drive predictable execution while maintaining high-quality standards.
Monitor team performance through quality metrics including: Automation coverage, Escaped defects, Defect trends, Test execution effectiveness, Release quality.
Use data to identify opportunities for continuous improvement.
Encourage experimentation with AI-driven productivity improvements and measure their impact.
Partner with Engineering Managers, Product Managers, Designers, and Developers to ensure quality is a shared responsibility.
Communicate testing progress, quality risks, and recommendations effectively.
Help development teams adopt practices that improve software quality from the earliest stages of development.