Senior/Tech Lead QA with AQA and AI experience

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

We're looking for a hands-on  Senior/Tech Lead 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.

Responsibilities:

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

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

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

Hands-on experience with test automation for web applications and/or APIs using tools or frameworks such as Playwright, Cypress, Selenium, pytest, or similar.

Ability to determine which test scenarios are suitable for automation versus manual validation.

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

Experience working in Agile/Scrum teams

Upper-Intermediate English or higher — you'll be communicating directly with the client and cross-functional team members

Familiarity with Palantir Foundry is a strong plus