Maneesh Sharma is the COO of LambdaTestan AI-native unified enterprise test execution cloud platform.
Is quality engineering (QE) an extension of software testing or a complete change in responsibilities? That’s a question I want to answer today.
As COO of an enterprise test execution cloud platform, where we process over a billion tests annually, I’ve seen how the demands on quality teams have accelerated alongside the technologies they support. So how can organizations use QE in a way that positions them to win rather than falling further behind?
Understanding Quality Engineering
The old models of software testing and traditional quality assurance (QA) typically treated testing as a final checkpoint before deployment. Engineers executed test scripts, documented defects and served as the last line of defense after developers finished coding. That approach worked when release cycles spanned months, but today’s continuous deployment schedules tend to make this method less effective.
Modern quality engineering embeds testing throughout the entire software development life cycle. QE teams collaborate with developers from the first design meeting through production deployment. They help shape architectural decisions based on testability concerns, write automation code alongside feature development, monitor production systems and feed performance data back into development priorities.
Quality engineers own outcomes instead of just test execution. They are responsible for deciding which metrics matter for product success, architecting test frameworks that scale with growing codebases, and implementing quality gates that prevent problematic code from reaching production. The role demands both technical depth and strategic thinking.
Objective Data On Adoption And Value
The quality engineering market is projected to grow from $54.68 billion in 2025 to $99.79 billion by 2035. That doubling reflects permanent changes in how organizations build software, not temporary trends or hype cycles.
Organizations back these investments with concrete action: 68% now integrate generative AI into their quality programs. These aren’t pilot programs or experiments; I’ve observed companies clearly restructuring entire departments around quality engineering principles.
How Testing Has Changed And The Practical Differences
Traditional testing operated sequentially. Developers wrote code, then testers validated it. Quality engineers, on the other hand, work in parallel with development teams. They review pull requests for testability issues. They pair-program test automation during feature development. They implement quality gates that prevent bad code from entering the main branch.
Consider how test creation has transformed. Manual testers once documented step-by-step instructions in spreadsheets. Quality engineers are expected to write code that tests code, build reusable test frameworks, implement design patterns and maintain test infrastructure. Their purpose is to treat test code with the same rigor as production code, including version control, code reviews and refactoring.
These approaches are backed by measurable outcomes. Organizations practicing modern QE in DevOps have seen “a 45% increase in deployment frequency, a 38% reduction in lead time for changes, and a 32% decrease in change failure rates.” These improvements can compound over time, creating competitive advantages that traditional testing typically cannot match. The value of these skills is reflected in the fact that QE engineers typically command higher salaries than traditional testers.
The Role Of AI And Automation In Today’s QE
Automation, data-driven decision-making and artificial intelligence now form the foundation of how QE teams operate. From the tech leaders I’ve talked to, QE teams are using AI to identify high-risk code changes that require additional testing, to generate test scenarios from requirements, and to predict likely failure points based on historical data. Machine-learning models are helping analyze millions of test results to optimize test selection and execution order.
This automation also extends beyond test execution. Quality engineers can automate environment provisioning, test data generation and results analysis. They can also build self-service platforms where developers trigger specific test suites on demand, as well as implement intelligent test selection that runs only relevant tests based on code changes, reducing feedback time from hours to minutes.
At my company, we see people running parallel test suites across thousands of browser and device combinations simultaneously. What once required weeks of manual testing can now be completed in under an hour. Automation can do more than just speed up existing processes; it can enable testing approaches that weren’t possible with manual methods.
Challenges Organizations Face When Adopting Quality Engineering
• Cultural Resistance
You may face resistance from developers and product managers unfamiliar with collaborative quality practices. Executives may also question increased quality budgets if they don’t see immediate ROI.
• Skill Gaps
Finding engineers who combine testing expertise with programming skills remains difficult. Training existing staff requires time and investment that many organizations hesitate to make. Python and JavaScript proficiency have become table stakes. To distinguish senior engineers from juniors, look for those with knowledge of CI/CD pipelines, container orchestration and cloud platforms. If your candidate has experience with performance testing, security testing and chaos engineering, consider offering them specialized roles with premium compensation.
• Technical Debt
Monolithic architectures are not ready for modern automation. Outdated tools don’t integrate with modern CI/CD pipelines, and organizations often attempt quality engineering transformations without addressing underlying architectural problems, leading to partial implementations.
• Choice Paralysis
Teams can struggle to choose between the hundreds of testing frameworks, platforms and services, and may experience integration challenges when combining tools from different vendors. License costs can also escalate as organizations add specialized tools for API testing, performance testing, security testing and visual testing.
Is quality engineering an evolution of the software testing role?
I believe the short answer is “yes.” But QE is not just a rebranding of QA. Quality engineering builds on the foundational skills of software testing but repositions them as part of a broader, more collaborative and more technical approach to building great software. I believe that those who step up to meet these new expectations could help shape how products are built in every industry that relies on software.
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