QA Software Test Automation Engineer - AI

QA Software Test Automation Engineer - AI

The Role:

We are looking for a QA Software Test Automation Engineer - AI to join our cutting-edge engineering organization and lead the adoption of AI technologies in software testing. This role is pivotal in transforming how we validate quality, performance, and reliability across our platforms by introducing AI-driven testing practices, while also investigating and standardizing methods for testing AI-based solutions themselves.

You will be responsible for driving AI-assisted quality engineering, developing intelligent test automation frameworks, and exploring the application of machine learning and generative AI for test generation, defect detection, and analysis. At the same time, you will evaluate and enhance the reliability of AI systems, ensuring they meet high standards for accuracy, fairness, and robustness.

The main responsibilities of the position include:

• Drive experimentation and implementation of AI and GenAI technologies in QA processes to enable intelligent test generation, prioritization, and maintenance
• Research, evaluate, and orchestrate next-generation Agentic QA frameworks and autonomous testing systems (e.g., TestMu AI, BlinqIO, or custom-built agentic workflows using Claude/Cursor/Github Copilot)
• Develop AI-augmented test automation frameworks capable of adapting to frequent product and UI changes (self-healing tests, smart locators)
• Implement AI-based analytics for root cause analysis, defect prediction, and quality risk assessment
• Define and refine strategies for testing AI-based solutions, including LLM-driven systems, agents, and ML models
• Design evaluation pipelines for AI components - measuring accuracy, robustness, fairness, explainability, and safety
• Collaborate with engineering, data science, and AI teams to integrate AI testing and AI-in-testing capabilities into CI/CD pipelines
• Stay at the forefront of emerging AI testing practices, driving innovation, experimentation, and education across QA teams
• Provide guidance and training to testers and engineers on how to leverage AI effectively in testing workflows

Main requirements:

• BSc/MSc in Computer Science, Artificial Intelligence, or related discipline
• 5+ years of hands-on experience in AQA
• 1+ years of experience applying AI or ML technologies in software testing or QA process improvement
• Proficiency in Python or JavaScript/TypeScript, with strong scripting and automation skills
• Experience with modern test automation frameworks (e.g., Playwright or similar)
• Familiarity with AI/ML workflows and tools (LLMs, vector databases, MLOps pipelines)
• Experience working in Docker/Kubernetes environments
• Understanding of AI-assisted testing approaches, such as:

o NLP-based test case generation

o Intelligent defect classification

o Model-based testing using AI

o Predictive quality analytics

• Familiarity with AI agent evaluation patterns (LLM-as-a-judge, human-in-the-loop)
• Proficiency with monitoring/observability tools such as Grafana, Prometheus, etc.
• Strong experience integrating tests into CI/CD pipelines (GitLab, Jenkins) and containerized environments (Docker, Kubernetes)

The following will be considered an advantage:

• Experience with gRPC, WebSockets, and HTTP/2
• Extensive experience with autonomous QA agents and agentic orchestration frameworks (e.g., LangChain, PydanticAI) to build self-evolving test suites that adapt to non-deterministic UI and logic changes
• Expertise in high-fidelity AI evaluation pipelines and real-time observability to measure probabilistic outcomes, including reasoning traces, and adversarial robustness
• Knowledge of AI ethics, fairness, and bias detection in model validation
• Familiarity with cloud-native AI solutions (AWS, GCP, Azure)

Benefit from:

• Attractive remuneration package
• Intellectually stimulating work environment
• Continuous personal development and international training opportunities

The Hiring Experience: What Awaits You

• Let’s Connect – Intro Chat with Talent Acquisition
• Deep Dive – First Interview with Your Future Team
• Final Connection – Final Interview

All applications will be treated with strict confidentiality!