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Зарплата не указанаРабота с GenAIКрупная компанияПроектный формат
Оценка от Hirify AI
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
GenAI Quality Engineer (m/f/d) (AI/LLM Testing): Validating AI-powered applications and AI-generated outputs while building automated testing solutions with an accent on probabilistic system quality, reliability, and performance. Focus on evaluating LLM responses, designing test cases and quality metrics, analyzing defects, and driving root cause resolution.
Location: Sofia, Bulgaria; hybrid work model with 3 days per week in the Sofia office.
Company
Tieto Tech Consulting provides design-led, data-centric, and AI-powered digital engineering and consulting services to enterprises worldwide and is part of hirify.global.
What you will do
Validate LLM-based applications and AI-generated outputs.
Evaluate the quality, reliability, and behavior of probabilistic AI systems.
Create test cases from evolving requirements and identify gaps, inconsistencies, and product risks.
Collaborate with product managers, engineers, and AI specialists throughout the development lifecycle.
Analyze defects, perform root cause analysis, and drive issue resolution.
Requirements
Experience testing AI-powered applications, GenAI solutions, chatbots, copilots, or similar products.
Understanding of AI/ML concepts and Large Language Models (LLMs).
Strong analytical and problem-solving skills.
Experience creating test plans, test cases, and quality metrics.
Excellent spoken and written English.
Nice to have
Experience with AI testing tools and frameworks.
Experience evaluating LLM responses for accuracy, relevance, safety, and consistency.
Familiarity with prompt engineering and AI quality assessment techniques.
Knowledge of Python or another programming language used in automation.
Experience working in Agile development environments.
Exposure to cloud platforms such as Azure, AWS, or GCP.
Culture & Benefits
Hybrid work arrangement with 3 office days per week in Sofia.
Work within a diverse, equitable, and inclusive environment.
Collaborate with a multinational team and specialists across engineering, product, and AI.
Hiring process
Discover and apply.
Interviews, assessments and tests, and background verification.
Offer and onboarding.
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