Driven by a passion for innovation and excellence in quality assurance, we are expanding our capabilities in AI-powered testing. As we continue to transform the way mobile applications and hardware-integrated systems are validated, we are looking for a Senior AI Test Engineer to join our dynamic QA team.
In this role, you will lead the development of intelligent test automation frameworks, integrating cutting-edge AI technologies to ensure robust, scalable, and efficient testing of mobile applications and hardware-in-the-loop systems. You will work closely with cross-functional teams to drive quality across the release chain and contribute to the evolution of testing excellence.
What You Will Do
AI-Powered Test Automation for Mobile Applications
Architect and implement a Retrieval-Augmented Generation (RAG)-based test automation framework using local LLMs (e.g., Ollama).
Build intelligent systems capable of reasoning about test requirements, analyzing app states, and generating dynamic test scenarios.
Develop AI-powered screenshot analyzers using Computer Vision (OpenCV) and OCR for precise UI validation.
Automate localization testing across languages and screen sizes using AI models to validate text, layout, and formatting.
Train models to detect UI anomalies, visual regressions, and inconsistencies beyond the scope of traditional tools.
Hardware-in-the-Loop (HIL) Testing Architecture
Design and develop a Python-based HIL framework for testing mobile apps integrated with proprietary medical hardware.
Build communication interfaces (USB, Bluetooth, Serial) to control and monitor device interactions during automated tests.
Train and deploy AI models that adapt to the unique behaviors of hardware interfaces for end-to-end system testing.
On-Premise Infrastructure Development for Scalable Test Execution
Deploy and manage local infrastructure for AI model inference, ensuring high performance and data privacy.
Containerize models and automation agents using Docker and integrate them into CI/CD pipelines (e.g., Jenkins, GitLab CI).
Build continuous learning loops that leverage test results and failure data to retrain and improve AI models.
AI and Open-Source Tooling Integration
Utilize open-source AI/ML libraries such as PyTorch, TensorFlow, Hugging Face, and scikit-learn for model development.
Extend or replace traditional frameworks like Appium with custom AI-assisted components.
Develop Python-based tooling for model training, inference, and integration into test workflows.
Experience
What you bring
4+ years of hands-on experience in software development with a strong focus on Python and AI/ML applications.
Proven expertise in building and fine-tuning models using PyTorch, TensorFlow, or Hugging Face.
Demonstrable experience with Computer Vision (OpenCV) and OCR for visual analysis and UI validation.
Strong background in building test automation frameworks and a clear understanding of the limitations of traditional tools like Appium.
Experience with CI/CD, Docker, and deploying ML models into production or testing environments.
Highly Desirable
Hands-on experience with local LLMs (e.g., Ollama, Llama.cpp) and RAG systems using LangChain or LlamaIndex.
Prior experience with Hardware-in-the-Loop (HIL) or Software-in-the-Loop (SIL) testing.
Familiarity with mobile development and testing ecosystems (Android/iOS).
Personal Competencies
A builder’s mindset with a drive to create innovative solutions.
Excellent problem-solving skills and the ability to navigate ambiguity.
Strong sense of ownership and ability to work independently.
Fluent and effective communication skills in English.
Who We Are
We are a forward-thinking team committed to redefining quality assurance through AI and automation. By combining deep technical expertise with a passion for innovation, we aim to build smarter, faster, and more reliable testing systems that support the next generation of mobile and hardware-integrated products.
Join us and be part of a team that values diversity, collaboration, and the pursuit of excellence.
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