Manager, AI-Native Quality Engineering

Libra Solutions, LP; Huntersville (NC); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Life insurance

401k match

Paid time off

Job summary

Libra Solutions seeks an experienced Manager, AI-Native Quality Engineering to lead a team focused on AI-powered test automation, regression efficiency, and release quality practices. This role collaborates closely with Engineering, Product, DevOps, and Release stakeholders to improve software delivery and build confidence in product quality.

The ideal candidate will drive AI-enabled automation, mentor engineers, and oversee testing across API, UI, integration, and end-to-end workflows to ensure

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent professional experience.
• 7+ years of experience in software QA, quality engineering, or test automation.
• 2+ years of people management or team leadership experience.
• Strong hands-on experience building, maintaining, and scaling automated tests.
• Experience evaluating AI assistants to accelerate test automation and improve workflows.

Responsibilities

• Lead a team of quality engineers, automation engineers, and testers.
• Drive AI-powered test automation across API, UI, integration, and end-to-end tests.
• Strengthen release readiness and quality outcomes through process improvements.
• Partner with Engineering, Product, DevOps, and Release stakeholders.
• Define quality metrics and drive continuous improvement initiatives.

Skills

AI test automation

Team leadership

QA automation

Test framework design

CI/CD pipelines

Education

Bachelor’s degree or equivalent

Tools

GitHub Copilot

Cursor

LLMs (Claude/ChatGPT)

Job description

About Us

When life gets hard, we make it easier! Libra Solutions helps overcome the burdens created by slow-moving legal processes. Combining technical innovation and financial strength, we help speed up cumbersome workflows and ease financial barriers for our customers.

Through the MoveDocs personal injury solutions platform, Libra integrates and streamlines medical, financial, and professional services for personal injury cases. Our mission is to help personal injury victims receive the medical care and personal funding needs they require, and to help streamline the process for the attorneys and medical providers that serve these victims. Libra operates under the MoveDocs, Oasis Financial and Probate Advance brands. We are proud of our mission and passionate about applying technology to the challenge of making healthcare more accessible.

Together, under the Libra Solutions banner, we have relationships with over 50,000 attorneys and over 12,000 healthcare providers nationwide, which gives us an amazing platform to service our customers.

Job description

The Manager, AI-Native Quality Engineering leads a team focused on improving software quality through AI-powered test automation, regression efficiency, and release quality practices. This role is expected to actively drive the use of AI tools to design, build, maintain, and execute automated tests across API, UI, integration, and end-to-end workflows.

The ideal candidate is a player-coach who can lead a team while staying close to the work. They will evaluate and implement AI tools that improve automated test creation, test maintenance, execution efficiency, defect analysis, and regression effectiveness, while also strengthening release readiness and overall quality outcomes. This role partners closely with Engineering, Product, DevOps, and Release stakeholders to improve software delivery and build confidence in product quality.

This position reports to the VP/Director, Engineering and can be based in any of our office locations in Denver, CO, Huntersville, NC, Rosemont, IL or Las Vegas, NV. We welcome strong remote candidates, with occasional travel to Las Vegas as needed.

Position Responsibilities

Team Leadership and People Management

• Manage, coach, and develop a team of quality engineers, automation engineers, and testers
• Set team priorities, goals, and expectations aligned to delivery and quality outcomes
• Support career development, performance management, and skill growth across modern quality engineering practices
• Foster a culture of accountability, continuous improvement, collaboration, and practical execution

AI-Powered Test Automation

• Drive the use of AI tools to design, generate, maintain, and execute automated tests across API, UI, integration, and end-to-end workflows
• Evaluate and implement AI-assisted capabilities that improve automation speed, coverage, stability, and maintainability
• Help establish practical standards and guardrails for the responsible use of AI in automated test development, execution, and defect analysis
• Help the team use AI to reduce repetitive manual work and improve automation effectiveness across the full test lifecycle
• Guide the application of AI to regression optimization, defect triage, failure analysis, and test maintenance

Automation and Quality Engineering

• Lead improvements to automated test frameworks and coverage across API, UI, integration, and end-to-end testing
• Stay hands-on with automation design, AI-assisted test generation, framework decisions, and workflow improvements
• Improve regression strategy by using AI and automation to better align test execution with product risk, release timelines, and quality goals
• Partner with engineers to embed AI-enabled automation and quality practices earlier in the development lifecycle
• Improve test reliability, maintainability, and signal quality to support faster and more confident delivery

Release Quality Management

• Support managed release quality processes, including test readiness, defect review, regression status, and go/no-go input
• Improve release confidence through better quality signals, risk assessment, and operational discipline
• Identify quality risks and
• Partner with engineering and release stakeholders to improve predictability and consistency in software delivery

Metrics and Continuous Improvement

• Define and track team-level quality metrics such as automation reliability, regression effectiveness, escaped defects, release readiness, and defect trends
• Use data to identify gaps, prioritize improvements, and communicate quality health to leadership
• Drive process improvements that increase efficiency, reduce risk, and improve customer-facing quality

• Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent professional experience
• 7+ years of experience in software QA, quality engineering, or test automation
• 2+ years of people management or team leadership experience
• Strong hands‑on experience building, maintaining, and scaling automated tests
• Strong experience with automation across API, UI, integration, and/or end‑to‑end testing
• Experience evaluating and using AI assistants such as Claude or similar tools to accelerate test automation and improve automation efficiency, quality engineering workflows, regression effectiveness, and release confidence
• Strong understanding of modern software development practices, CI/CD pipelines, and agile delivery environments
• Experience in SaaS or modern product‑based software environments
• Experience partnering closely with engineering, product, and business stakeholders in an agile delivery environment
• Demonstrated ability to lead, develop, and retain a high‑performing quality engineering team
• Strong problem‑solving, communication, organizational, and coaching skills
• Experience coaching teams through process and tooling changes
• Highly proficient with AI coding assistants (GitHub Copilot, Cursor) and general‑purpose LLMs (Claude, ChatGPT, Azure OpenAI) with a demonstrated commitment to building AI‑native quality engineering practices and tools evaluation; able to coach quality engineers on effective prompt engineering, AI output evaluation, and responsible AI use
• Prompt engineering proficiency: able to design reusable prompt templates and system instructions for common quality engineering workflows such as test case generation, test data scaffolding, defect analysis, and regression planning
• Skilled at critically evaluating AI-generated test output for correctness, coverage quality, and false confidence patterns; able to identify where AI-generated tests assert the right form but wrong behavior, and guide the team on what to watch for
• Experience leading teams within agentic or AI‑accelerated delivery models, or a clear understanding of how agentic workflows change team rhythms, role expectations, and quality ownership when AI agents are contributing to both code and test generation at scale.
• Must be authorized to work in the U.S.

Libra Solutions offers competitive compensation and benefits that include medical, dental, vision and life insurance plans, plus a 401k match and paid time off.