Join Horizons – the team exploring and building AI-powered products that don’t have industry playbooks yet.
As a Horizons Quality Engineer, you won’t just test features – you’ll define what “correct” means for AI systems that didn’t exist three months ago. This isn’t a traditional QE role with predefined test cases or stable requirements. You’ll operate in high ambiguity, where the product evolves weekly and the rules are still being written.Your impact will go beyond finding bugs – you’ll shape how we evaluate AI at Hostinger, define best practices, influence product decisions, and raise the quality bar for intelligent tools used by millions.
This role is for someone who sees ambiguity as opportunity, not chaos – someone who doesn’t wait for documentation, but creates it, and who builds confidence in the future of our AI products.
Curious to learn more? Connect with your team: Aurimas Karlonas, QA Lead

Your day-to-day:
• Define success criteria for AI-driven features where no industry standards exist, and clarify what “correct” truly means.
• Design and execute testing strategies for AI tools, including exploratory and adversarial testing to uncover failure modes.
• Develop evaluation frameworks to measure AI behavior – accuracy, consistency, hallucination rate, edge-case handling, and stability.
• Build and maintain testing datasets, validation pipelines, and experimentation frameworks.
• Identify patterns in AI behavior, developing intuition around its strengths, weaknesses, and risk areas.
• Act as the voice of quality strategy, bridging the gap between what we build and how we know it’s truly good.

Your skills and experience:
• 4+ years of experience in software quality engineering (experience with AI-powered products is a strong plus).
• Strong critical thinking – you reason from first principles, not templates.
• Experience in web testing and automation (Playwright, Cypress, Selenium, or similar), with strong programming skills (TypeScript is a plus) and confidence working with APIs, logs, debugging tools, and data.
• Experience with API manual testing and automation (Postman, Rest Assured, Swagger, or similar tools).
• Experience with Database (MySQL or similar).
• Ability to define and measure quality beyond “it works,” including meaningful metrics and evaluation criteria.
• Strong interest in how AI systems work under the hood, with the curiosity to quickly learn new tools and technologies.
• Comfortable operating in ambiguity – no documentation, no prior art, no one to ask.
• Proactive, analytical, and persistent, with strong communication skills in English (Lithuanian is a plus).

What makes you stand out:
• Hands-on experience testing LLM-based or AI-driven systems, including prompt engineering and working with evaluation datasets or benchmarking methods.
• Strong understanding of AI failure modes (hallucinations, bias, drift, ed