Requirements and responsibilities

Job Description: AI-Native QA Manager

Position Summary

We are looking for an AI-Native QA Manager to transform how software quality is delivered. This is not a traditional QA leadership role—we're looking for someone who has already demonstrated measurable improvements in QA productivity, quality, and speed through the practical application of AI, automation, and modern engineering practices.

You'll lead a team responsible for quality across multiple SaaS products while fundamentally rethinking how testing is performed. We expect you to leverage AI agents, intelligent test automation, autonomous testing frameworks, and modern CI/CD practices to dramatically increase engineering velocity without compromising quality.

Experience in Life Sciences, Healthcare, Medical Devices, or other regulated software environments is highly desirable.

What You'll Do

AI-Driven QA Transformation

• Develop and execute an AI-first strategy for software quality.

• Introduce AI tools that significantly improve test creation, maintenance, defect detection, regression testing, and release confidence.

• Evaluate and implement emerging AI QA platforms, coding assistants, autonomous testing tools, and agentic workflows.

• Continuously measure productivity gains and quality improvements from AI adoption.

QA Leadership

• Lead, coach and develop a distributed QA team.

• Establish quality standards across manual, automated, API, integration, UI and performance testing.

• Drive automation-first thinking while eliminating low-value manual work.

• Build scalable QA processes that support rapid software delivery.

Engineering Collaboration

• Partner closely with Engineering, Product Management and DevOps.

• Embed quality throughout the SDLC rather than treating QA as a downstream gate.

• Improve developer feedback loops through automation and intelligent tooling.

• Champion shift-left testing practices.

Modern Test Automation

• Improve automation coverage and reliability.

• Reduce regression execution times through intelligent automation.

• Build maintainable test frameworks integrated into CI/CD pipelines.

• Increase release confidence through automated quality metrics.

Metrics & Continuous Improvement

Own metrics such as:

• Test automation coverage

• Defect escape rate

• Mean time to detect defects

• Regression execution time

• QA cycle time

• Release quality

• Productivity improvements from AI

• Cost per release

• Manual effort eliminated

What We're Looking For

Required

• 7+ years in Software QA, including leadership experience.

• Demonstrated success improving QA productivity through AI, automation, or modern engineering practices.

• Experience leading QA teams across multiple products.

• Strong understanding of modern software development practices and CI/CD.

• Experience with API, UI, integration and end-to-end testing.

• Strong analytical and problem-solving skills.

• Comfortable working in fast-moving SaaS environments.

AI Experience (Highly Important)

You should have practical experience using tools such as:

• GitHub Copilot

• Cursor

• Claude

• ChatGPT

• AI coding agents

• AI test generation platforms

• Autonomous testing tools

• AI-assisted debugging

• AI-assisted root cause analysis

We're interested in measurable outcomes, not simply familiarity with AI.

Examples include:

• Reduced regression effort by 70%

• Increased automation coverage from 40% to 90%

• Doubled QA throughput

• Reduced escaped defects

• Built AI workflows that replaced repetitive manual testing

Bonus Experience

Strong preference for candidates with experience in:

• Life Sciences software

• Clinical software

• Medical Affairs platforms

• GxP environments

• FDA-regulated software

• ISO 13485

• IEC 62304

• HIPAA

• SOC 2

• Other regulated industries (banking, aviation, insurance, government)

What Success Looks Like (First 12 Months)

Within your first year, you will:

• Increase QA team productivity by 2–5x through AI and automation.

• Significantly reduce manual regression testing.

• Improve release confidence while increasing release frequency.

• Implement AI-assisted test generation and maintenance.

• Embed quality throughout the SDLC rather than relying on end-of-cycle testing.

• Establish clear quality metrics and executive dashboards.

• Build a culture where QA engineers leverage AI as a core part of their daily workflow.

Why Join Us

You'll have the opportunity to reshape software quality from the ground up across a growing portfolio of SaaS products. We believe AI is fundamentally changing software engineering, and we want QA to lead that transformation—not follow it.

If you're excited about replacing repetitive work with intelligent automation, building AI-enabled teams, and delivering higher-quality software faster, we'd love to hear from you.