Manager, AI-Native Quality Engineering

Libra Solutions

. Lead and develop a team of quality engineers, automation engineers, and testers .

Posted 9/17/2026full-timeColorado • United StatesSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading quality engineering teams, implementing AI-assisted automation strategies, and ensuring high-quality software delivery through effective test management and metrics tracking. Proficient in modern software development practices and agile methodologies, with a strong focus on automation across various testing domains.

Highest-signal resume keywords

AI-Powered Test AutomationQuality Engineering LeadershipAutomated Testing Across API, UI, IntegrationCI/CD Pipeline ExperienceAI Coding Assistant Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Test AutomationQuality AssuranceRegression StrategyDefect AnalysisAutomation Framework DevelopmentAI-Assisted TestingPrompt EngineeringData-Driven Quality MetricsAgile Delivery PracticesSaaS Environments

Soft Skills

Problem-SolvingCommunicationOrganizational SkillsCoachingTeam Leadership

Tools & Technologies

GitHub CopilotClaudeChatGPTAzure OpenAICursor

Industry Keywords

Software Quality AssuranceTest AutomationAgile MethodologiesAI-Accelerated DeliveryQuality Metrics

Tech Stack

Tools & technologies

Azure

About the role

Key responsibilities & impact

Lead and develop a team of quality engineers, automation engineers, and testers
Set team priorities, goals, and expectations aligned with delivery and quality outcomes
Drive AI-powered design, generation, maintenance, and execution of automated tests across API, UI, integration, and end-to-end workflows
Evaluate and implement AI-assisted capabilities to improve automation speed, coverage, stability, and maintainability
Establish standards and guardrails for responsible AI use in test development, execution, and defect analysis
Guide AI use for regression optimization, defect triage, failure analysis, and test maintenance
Lead improvements to automated test frameworks and coverage
Stay hands-on with automation design, AI-assisted test generation, framework decisions, and workflow improvements
Improve regression strategy based on product risk, release timelines, and quality goals
Partner with engineers to embed AI-enabled automation and quality practices earlier in the development lifecycle
Support release quality processes, including test readiness, defect review, regression status, and go/no-go input
Identify quality risks and escalate issues with recommendations and supporting data
Define and track quality metrics, including automation reliability, regression effectiveness, escaped defects, release readiness, and defect trends
Use data to prioritize improvements and communicate quality health to leadership
Report to the VP/Director, Engineering

Requirements

What you’ll need

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
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, including GitHub Copilot and Cursor, and general-purpose LLMs, including Claude, ChatGPT, and Azure OpenAI
Ability to coach quality engineers on prompt engineering, AI output evaluation, and responsible AI use
Ability to design reusable prompt templates and system instructions for quality engineering workflows
Ability to critically evaluate AI-generated test output for correctness, coverage quality, and false confidence patterns
Experience leading teams within agentic or AI-accelerated delivery models, or clear understanding of how agentic workflows change team rhythms, role expectations, and quality ownership
Must be authorized to work in the U.S.

Benefits

Comp & perks

Medical insurance
Dental insurance
Vision insurance
Life insurance
401k match
Paid time off
Remote work option with occasional travel to Las Vegas as needed