You’ve likely noticed a change in how software quality is handled across many engineering organizations. Large, centralized QA teams are no longer as common. The title “QA Engineer” appears less often on org charts.
In fact, TESTINGMIND reports that medium and large organizations typically maintain just 1-3 QA engineers per 10 developers. In smaller teams, QA may be even less, with 25.6% of small orgs reporting fewer than 1 QA for every 10 developers.
Instead, more responsibilities are now shifting to product developers, platform engineers, and Site Reliability Engineers (SREs). This reflects a deliberate shift toward “quality built in” rather than “quality tested in at the end.”
QA Engineer Role Is Disappearing
The reason is apparent: today, most teams ship continuously. Code is merged multiple times a day, infrastructure is defined and managed as code, and testing infrastructure is built alongside systems with the expectation that failures will occur and can be recovered from quickly. In a nutshell, ensuring software quality is a distributed function.
So is the QA engineer role disappearing? Not exactly. But it’s definitely changing. This blog post dissects that perspective in detail.
What’s Driving the Change in the Delivery Environment?
1. Toolchains support continuous validation
Previously, environments for testing were challenging to replicate, and tool support was fragmented. Today, modern toolchains enable you to validate changes in real-time. Unit and integration tests, static analysis, and runtime checks can all be triggered by CI/CD pipelines.
This setup makes it practical to move responsibility for quality closer to those writing the code.
What to watch out for:
CI pipelines run on every merge and block on failing tests
Code coverage reports and static analysis results are visible and acted on
Teams can spin up production‑like test environments without waiting on ops
Pro Tip: Regularly review pipeline execution times and test coverage by team to ensure optimal performance. Track metrics like test run times, flaky test rates, and pass/fail trends to guide improvements.
2. Delivery speed has outgrown late-stage testing
Release cycles are shorter. Teams that used to ship quarterly now deploy production multiple times a day. A manual QA phase that once took days or weeks is no longer viable. Quality controls must run in parallel with development, starting at the first commit.
What to watch for:
Developers merge only after unit and integration tests pass in CI
Backlog items include explicit test criteria before work starts
Defects caught after deployment trend down over time
Pro Tip: Make test planning part of backlog planning. Acceptance criteria should describe both functionality and how it’ll be validated.
3. Developers are better positioned to own quality
According to the State of Frontend 2024 research:
- 44.7% of teams share testing between developers and QA
- 22.4% rely mostly on developers for testing
- Only 10.3% mainly use QA, and just 2.3% rely on QA alone In this day and age, developers already possess a deep understanding of their code and its intended behavior. They’re best placed to embed safeguards early. When they own test coverage and respond directly to failures, defects surface sooner, and recovery is faster.
Giving developers ownership minimizes handoffs and creates more transparent accountability.
What to watch for:
- Code review checklists include verification of test coverage and risk areas
- Teams actively track and improve flaky or brittle tests as part of everyday work
- Post-incident reviews result in new automated tests added by the team, not by a separate group
Pro Tip: Use code review checklists that include test expectations to ensure thorough code review. A pull request without appropriate tests should not pass.
4. Cloud-native systems require quality in production
Modern systems are distributed, dynamic, and constantly evolving. Certain classes of failures only emerge under real load. Quality practices extend into production with techniques like:
- Automated rollback policies
- Canary deployments
Feature flags
What to watch for:SLOs and error budgets are defined per service
Automatic rollbacks triggered by health check failures
Chaos experiments or failure injection exercises run as part of normal operations
Pro Tip: Incorporate automated health checks and SLI (Service Level Indicator) validations into deployment pipelines. Block or roll back a release automatically when thresholds aren’t met.
Quality Ownership and Delivery Trends
The following metrics confirm how teams are adapting and where senior QA professionals can focus their influence:
What’s Next: Steps Engineering Leaders Need to Take
The transition away from traditional QA models doesn’t happen organically. You must be directly involved in changing how teams are staffed, testing is supported, and quality is measured. Your core responsibility is to enable your team. Here’s how you can do that:
1. Re-scope quality ownership
Take a close look at how teams are organized. Update developer, platform, and SRE roles to include test design, CI/CD ownership, and operational validation as part of their daily work. Your teams need engineers who can build and validate.
That includes writing tests, debugging failures, and understanding where quality breaks down under load or edge cases. Therefore, hire for testing fluency.
Pro Tip: Run a skills and responsibilities review this quarter. Determine which QA functions can be integrated directly into engineering teams and identify where new tooling or hiring/coaching support is needed.
2. Invest in test infrastructure
Capgemini reports 96% of organizations
include cloud testing as part of their testing lifecycle (57% for most projects, 39% for some).
If you want teams to own quality, they need reliable tools that keep up with delivery speed. Slow pipelines and flaky tests break confidence and delay releases. However, having too many tools isn’t always positive. An extensive stack can hide accountability.
The key is to choose a small set of testing and deployment tools that work well together and are easy to maintain. Leverage new capabilities like AI-driven test generation or failure analysis. Conduct a pilot test using a focus group of engineers to assess their response to the latest tools.
Pro Tip: Run a tooling review before your next budget cycle. Identify overlap, remove tools you no longer need, and plan investments where automation can make the biggest difference.
3. Collapse handoffs
Handoffs, too, create delay, confusion, and diluted accountability.
The more distance between the person writing the code and the person validating it, the harder it becomes to maintain quality at speed. Therefore, encourage teams to self-test before review. Align quality responsibilities with delivery milestones.
Pro Tip: Build quality checks directly into pull request workflows. Automate as much of the review process as possible using static analysis, test coverage checks, and approval gates tied to CI status.
4. Align metrics and incentives
Look at how you measure progress. Bug counts and sign-offs rarely indicate whether your systems are resilient. Track things like test coverage trends, time to defect, defect escape rates, time to recover, and how often you roll back a release.
Pro Tip: Create a dashboard that displays these metrics at the leadership level. Review them regularly and use them during planning cycles to guide improvements.
Bringing it all together
The shift you are seeing in your teams is mirrored across the industry. Quality is moving closer to the people building and running the systems, and the QA engineer role is evolving into something broader and more integrated.
Investing in the right platforms makes this shift practical.
An end-to-end AI-powered testing platform, like TestGrid.io, gives your teams access to real devices and browsers for cross-platform testing without the need to maintain internal labs or complex infrastructure.
They can run automated and manual tests in parallel, feed results directly into CI pipelines, and avoid the maintenance burden that often slows QA or DevOps. When you remove friction like this, it becomes easier for every engineer to take responsibility for quality.
That is what keeps quality distributed, embedded, and sustainable as you scale.
This blog is originally published at Testgrid
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