Team Spotlight: Evgeniy, Head of QA at Scalable

Welcome to Team Spotlight, a series where we look behind the scenes at Scalable to talk with the people shaping our technology, product, and culture.

In this edition, we sit down with Evgeniy, Head of QA. Evgeniy reflects on his transition from business analysis to engineering management, explains how QA acts as a support system for the entire product team, discusses practical AI applications in testing, and shares his perspective on working at Scalable.

Evgeniy, to start with the fundamentals: how do you define the role of QA?

I see QA primarily as a supporting function that helps everyone else do high-quality work without unnecessary stress.
Here is a practical example: when something breaks in production at 3:00 AM, it is usually a developer who gets called to fix it. Our job in QA is to help that developer release a product they feel confident in, so they can sleep through the night without emergency alerts. The same logic applies to design, product analytics, and architecture. QA exists to back up our teammates and give the whole team confidence in what we release.

How did your journey into QA start, and what led you into management?

I started my career as a business analyst at a startup. We had an experienced QA engineer on the team who tested the mobile app while teaching me backend testing techniques.

When that startup reached its end, I decided to give testing a try, and it turned out to be a great fit. Over time, doing repetitive manual checks became tedious, so I shifted my focus to test automation. The leadership noticed my facilitation and communication skills and suggested I try stepping into Scrum Master and Team Lead roles.

What do you enjoy most about engineering management?

The scale of impact. Working as an individual contributor lets you solve local problems. Leading a team allows you to tackle bigger initiatives. When you lead an entire department, you can design systemic solutions and make lasting improvements across the organization. That scale and visible impact are what motivate me most.

How do you disconnect outside of work?

Many of my colleagues know that I am a Candidate Master in draughts (checkers), which is great practice for strategic thinking and focus.

I also enjoy community building — after relocating, I set up a local QA community in Montenegro. We get together offline to exchange ideas, talk shop, and discuss industry trends.

What is your vision for a strong QA department, and what is your team working on today?

My philosophy is that automation must keep pace with software development, not lag behind it. You should never be in a position where you are trying to automate yesterday's work while new features keep piling up.

Right now, we are refining our testing infrastructure across dev and staging environments. The goal is to ensure automated test suites run quickly and reliably on every merge request, making the feedback loop transparent and predictable for engineers.

We are also making practical progress with AI. In many interviews, I hear candidates describe AI as just an advanced search tool or code autocomplete. We build applied engineering tools around it. For instance, we developed an internal bot that automatically parses and analyzes automated test run results. We focus on building tools that solve real operational friction.

Are there practices within QA that other teams could adopt?

Crowd testing is a great example. Before a major release, a group of colleagues runs through a feature together. A fresh perspective helps catch subtle issues within 15 to 20 minutes. It is a straightforward approach that works just as well for product analytics, design, and development teams.

How do you see cross-functional collaboration evolving?

We want our teams to work in genuine symbiosis. We should avoid scenarios where developers finish a task, throw it over the wall, and leave QA to figure it out alone. A healthy engineering process is a partnership: developers cover core test scenarios early, while QA builds the test model and environment in parallel.

As AI tools continue to accelerate development cycles, synchronous collaboration becomes even more important. When specialists collaborate from the early stages of a task, delivery is faster and overall quality is higher.

Looking at your time at Scalable, what stands out compared to other places you have worked?

First and foremost, the people. We have a strong, motivated team focused on shared goals. The leadership maintains a healthy balance between autonomy and accountability, with clear standards and trust in people's expertise.
The technology stack is modern and actively maintained. What stands out to me is how the company approaches legacy systems: instead of ignoring legacy code or just complaining about it, teams have concrete modernization plans and execute on them steadily.

There is also genuine encouragement around AI experimentation, and teammates are eager to learn and try new tools.
Finally, the office environment deserves a mention – it is comfortable, well-thought-out, and genuinely a great space to spend time when working on-site.

If this is how you think about work, we'd like to meet you. Open roles at Scalable