Helika builds AI-powered characters and publishing infrastructure for entertainment, brands, and game studios, helping them engage players directly inside communities where they already spend time.

We are looking for someone who genuinely cares about what ships and is ready to take responsibility for the product experience end-to-end. This role covers both traditional software testing and AI/LLM feature validation, making it a unique and important position in our team.

Responsibilities:

• Own overall product quality: define and implement the testing strategy, decide where automation pays off, where manual testing is sufficient, and where production monitoring is the right answer.
• Participate in grooming, planning, and sprint ceremonies - not as an observer, but as the person who surfaces risks and asks the hard questions before a line of code is written.
• Communicate risks clearly to developers, product managers, and stakeholders. Be able to make a case for blocking a release when something isn’t ready, and explain it in a way that lands.
• Prioritize defects by risk and business impact, not just log everything. Help the team understand what needs to be fixed now, what can wait, and what is safe to ship.
• Test and evaluate AI agents and LLM features: validate prompt behavior, catch hallucinations and model regressions, cover edge cases in agentic flows.
• Use observability tools - LangSmith, LangFuse, or equivalents - for agent tracing, prompt quality analysis, and production issue detection.
• Perform functional, regression, UI/UX, and exploratory testing of the web application.
• Run API testing using Postman, Swagger, or scripts - and investigate issues independently without waiting on a developer.
• Provide feedback on usability, accessibility, and system performance. You are the last line of defense before the user.
• Propose and drive improvements to QA processes, release flows, and the broader quality culture of the team.

Requirements:

• 5+ years in QA with experience owning product quality.
• Solid understanding of AI/LLM testing: you know that a prompt change can break behavior, that model outputs require evaluation criteria, and that “sometimes gives a weird answer” is a real bug that needs a real strategy.
• Strong manual testing fundamentals and hands-on experience with test design techniques - knowing when to explore, when to follow a plan, and when you can skip both.
• Practical API testing experience: comfortable reading logs, querying data, and diagnosing issues without help.
• Solid understanding of SDLC and Agile - sprint ceremonies feel like useful work, not overhead.
• Risk-oriented mindset: prioritize by impact, avoid blocking releases over cosmetic issues, and be able to articulate go/no-go decisions clearly.
• Ability to create clear and useful test documentation - test plans, test cases, and bug reports that actually help, not just check a box.
• English B1+ (written and spoken)

Nice to Have:

• Experience with LangSmith, LangFuse, or other LLM observability and evaluation tools.
• Python automation experience - ability to design, write, and maintain tests, not just run them.
• Hands-on experience building eval datasets and evaluation criteria for AI outputs.
• Familiarity with AWS/GCP and related tools and services.
• Familiarity with AWS and related tools and services.
• Experience as the sole or primary QA on a product team.

What We Offer:

• Fully remote
• Flexible schedule
• Paid time off: 15 working days of vacation and 5 additional days off per year
• Public holidays according to your country
• Career growth opportunities
• No bureaucracy - a results-oriented team with genuine flexibility
• Compensation aligned with your experience and expectations