Senior QA Engineer – AI Systems & Distributed Platforms

Talent Quanta is seeking a Senior QA Engineer – AI Systems & Distributed Platforms fluent in English, to offer his/her services as an expert who will be based in Luxembourg , Luxembourg. The work will be carried out either in the company’s premises or on site at customer premises. In the context of the first assignment, the successful candidate will be integrated in the Development team of the company that will closely cooperate with a major client’s IT team on site.

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