Tech Lead/Senior QA Engineer with AI experience

N-iX is looking for a Tech Lead/Senior QA Engineer with AI experience to join our team.

We're looking for a hands-on Tech Lead/Senior Manual QA Engineer who can cover the full testing spectrum: UI, API, and AI/ML output validation. You'll be joining a project building an AI-powered document analysis platform from the ground up. The system combines a CMS backend, modern UI, and a RAG-based AI layer used for intelligent document processing and analysis.

Key Responsibilities

• Follow a phased QA approach — begin with CMS and backend testing to establish a reliable baseline of expected system behavior, then apply those insights to validate AI agent outputs effectively


• Design and execute test cases for REST APIs, covering functional correctness, edge cases, error handling, authentication, and data integrity


• Perform UI testing across core user journeys, validating layout, behavior, and integration with backend services


• Transition into AI output validation once the deterministic layers are stable — using your knowledge of business rules to identify inconsistencies, hallucinations, or degraded outputs in agent responses


• Document and maintain test cases, test plans, and bug reports in a structured and traceable way


• Participate in requirement reviews and technical discussions to identify testability gaps early


• Collaborate with the Lead Big Data/AI Engineer and AI team to understand RAG pipeline behavior, document ingestion flows, and output quality expectations


• Contribute to building reusable test assets and QA processes as the project scales

Requirements

• 4+ years of experience in manual QA, with exposure to frontend, backend and AI testing


• Solid experience with API testing using tools such as Postman, REST Client, or similar


• Experience testing web UIs and understanding of cross-browser/cross-environment considerations


• Ability to read and interpret API documentation, data schemas, and system architecture descriptions


• Hands-on experience working on projects that included AI, ML, or NLP components — particularly validating outputs that are probabilistic or context-dependent


• Familiarity with the concept of RAG (Retrieval-Augmented Generation) or LLM-based systems


• Strong analytical thinking — especially the ability to assess whether an AI response is contextually correct, not just technically non-null


• Good understanding of test documentation practices: test plans, test cases, bug reports, traceability


• English level at least Upper-Intermediate

We offer*:

• Flexible working format - remote, office-based or flexible


• A competitive salary and good compensation package


• Personalized career growth


• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)


• Active tech communities with regular knowledge sharing


• Education reimbursement


• Memorable anniversary presents


• Corporate events and team buildings


• Other location-specific benefits

*not applicable for freelancers