RMT Labs S.A.
Luxembourg, LUXEMBOURG
Senior QA Engineer – AI Systems & Distributed Platforms
Core Technical Requirements
• Strong experience in software quality assurance for complex distributed systems
• Experience designing and maintaining automated test frameworks
• Strong understanding of: backend architectures, frontend architectures, microservices-based systems
• Ability to test APIs, event-driven systems, and distributed workflows
• Deep understanding of system behavior under load and failure scenarios
AI-Assisted Testing & Tooling
• Strong experience using AI-assisted development tools: Cursor, Claude Code
• Experience using AI tools for: test generation, test refactoring, test optimization
• Familiarity with self-healing / self-fixing test platforms
• Ability to design AI-supported QA workflows that increase speed and coverage
• Experience evaluating AI system behavior beyond deterministic outputs
Frontend & Backend Testing
• Strong experience writing: end-to-end tests, integration tests, functional tests
• Experience with modern E2E frameworks (e.g., Playwright, Cypress or similar)
• Experience testing REST APIs and asynchronous systems
• Understanding of frontend rendering flows, state management, and API integration
• Ability to validate complex UI flows involving ranked results and AI explanations
Distributed Systems & Event-Driven Testing
• Understanding of microservices architecture and distributed communication
• Experience testing event-driven systems using Kafka
• Knowledge of: asynchronous processing, retries, eventual consistency, idempotency
• Ability to validate data pipelines supporting search, ranking, and feature computation
• Experience testing systems deployed in containerized environments (Docker, Kubernetes)
AI & Ranking System Awareness
• Basic understanding of: machine learning pipelines, ranking systems, hybrid search
• Ability to test non-deterministic systems (LLM outputs, ranking variance)
• Experience designing validation strategies for: ranking outputs, explanation layers, scoring consistency
• Understanding of evaluation metrics (NDCG, Precision@K) is a strong plus
• Ability to distinguish between system failure and acceptable model variance
Cloud & Infrastructure Testing
• Experience testing applications deployed on cloud providers (AWS, GCP, or Azure)
• Familiarity with CI/CD pipelines and automated test integration
• Understanding of performance testing, load testing, and reliability testing
• Ability to design regression testing strategies for distributed AI systems
Product & Ownership Mindset
• Thrives in high-paced startup environments
• Strong ownership mindset - ensures system quality end-to-end
• Comfortable working with evolving AI systems and ambiguous requirements
• Proactive in identifying architectural risks and edge cases
• Understands the business impact of ranking errors or system instability
• Collaborates closely with frontend, backend, and ML engineers
Senior-Level Expectations
• Designs QA strategy, not just test cases
• Defines quality standards for AI-powered systems
• Establishes testing frameworks for hybrid search and ranking systems
• Balances speed of delivery with system reliability
• Builds scalable QA processes that evolve with the product
Impostato 2 settimane fa