QA Tech Lead (all genders)

You will establish and scale Quality Assurance as a cross-cutting engineering capability across multiple cross-functional Scrum teams. In a matrix organization with distributed QA capacity, your mission is to:

Enable teams to own quality end-to-end

Build a scalable QA platform and operating model

Drive automation, AI adoption, and engineering best practices

You act as a Functional Lead for QA Engineering. QA Engineers are embedded in cross-functional Scrum teams, working alongside Lead Developers, Software Engineers, DevOps Engineers and Technical Product Managers. You ensure alignment, standards, and quality consistency across all teams.

QA Strategy & Operating Model

Define and implement a scalable QA operating model across multiple teams

Establish clear QA standards, processes, and governance

Balance team autonomy with centralized QA best practice

Continuously evolve QA as a platform capability within Engineering

Cross-Team Leadership in a Matrix Organization

Lead QA engineers across multiple cross-functional teams (functional leadership)

Ensure consistent QA practices, tools, and quality standards across all teams

Act as the central point of coordination for QA topics across engineering

QA Enablement & Shared Ownership of Quality

Enable development teams to take shared ownership of quality (shift-left)

Collaborate closely with Lead Devs, DevOps Engineers, Technical Product Managers

Provide training, coaching, and guidelines for QA best practices

Reduce dependency on centralized QA execution through enablement

Automation & QA Platform Engineering

Design and drive test automation strategies (smoke, regression, API, E2E)

Build reusable QA frameworks and integrate them into our Engineering Platform

Integrate automated testing into CI/CD pipelines (Azure DevOps, YAML)

Ensure scalability and maintainability of automation across teams

AI-driven QA Innovation

Evaluate and implement AI-powered QA solutions, such as:

Test generation

Regression automation

Test coverage analysis

Use AI to improve efficiency and scalability of QA across multiple teams

Quality Engineering & Governance

Define and enforce quality gates (e.g. SonarQube, pipeline checks)

Establish and track QA metrics (coverage, defects, release quality, etc.)

Implement monitoring, logging, and feedback loops for production quality

Ensure robust systems via performance, load, and security testing strategies

Team Development & Scaling

Build and develop the QA team as it grows

Define specialization areas (e.g. automation, performance, exploratory testing)

Mentor QA engineers and support their career growth

Ensure high-quality execution and continuous improvement of QA practices

MUST HAVE

5+ years of experience in Quality Assurance and Software Engineering

Proven experience in leading QA across multiple teams or products

Strong expertise in test automation and QA architecture

Experience working in a matrix organization and cross-functional teams

Deep understanding of modern QA methodologies, tools, and processes

Hands-on experience with CI/CD and automated testing integration

Strong engineering background (ideally .NET / C# and distributed systems)

Experience with AI-driven QA tools or strong interest in applying AI in QA

GOOD TO HAVE

Experience with:

Test automation frameworks (e.g. Playwright, Selenium)

API testing (e.g. Postman)

Performance testing (e.g. JMeter, Azure Load Testing)

Cloud architectures (Azure, microservices, serverless)

Modern engineering platforms and internal developer portals (e.g. Port.io, Backstage).

WHAT SUCCESS LOOKS LIKE

Within the first 6–12 months:

A clearly defined and adopted QA operating model across all teams

Consistent QA practices and standards across the organization

Significantly increased automation coverage and CI/CD integration

Development teams actively owning and executing quality practices

Successful introduction of AI-supported QA workflows

Quality Metrics and regular reporting

Improved product stability, performance, and release quality