Infrastructure and Automation Test Engineer
Neureality
Other Engineering, Quality Assurance
Israel
Posted on Jul 16, 2025
Infrastructure and Automation Test Engineer
- System Integration
- Israel
- Senior
- Full-time
Description
NeuReality's software department is looking for an experienced and highly motivated Infrastructure and Automation Test Engineer to join us and be part of NeuReality’s next-generation, state-of-the-art AI inference server development.
The group designs, develops, validates, and releases inference server and programming SDK software products to make AI deployment easy and cost/power-effective.
Responsibilities:
- QA activities that are required for releasing high-quality products to NeuReality's customers.
- Tight collaboration with architects and development teams.
- Reviewing specifications and technical design documents to provide timely and meaningful feedback.
- Creating product test plans and managing their execution.
- Defining metrics for quality evaluation.
- Design and development of new automatic testing approaches for various features and products developed by NeuReality.
- Consistently reviewing, analyzing, and improving test automation infrastructure and reports.
Requirements
- BSc in Computer Engineering / Computer Science / Electrical Engineering
- 5+ years’ experience in developing automation/validation products with Python as a leading language.
- Experience in infrastructure development (e.g., test environments, test execution frameworks, reporting tools)- Must!
- Experience in validation of complex systems and performance tests.
- Formal and practical knowledge of testing methodologies.
- Hands-on expertise in test writing and automation.
- Excellent knowledge of Linux operating system and good understanding of networking.
- Level of exposure to cloud capabilities, including Kubernetes, virtualization, Docker, etc.
- Proficiency in test automation tools and frameworks (e.g., PyTest, TestNG, JUnit).
- Familiarity with version control systems (e.g., Git) and CI/CD pipelines (e.g., Jenkins, GitHub).
Problem-Solving and Analytical Skills
- Ability to identify, analyze, and debug issues within complex systems, including AI pipelines.
- Knowledge of data validation and techniques to test AI fairness, bias, and performance.
- Communication and Teamwork
- Strong verbal and written communication skills for collaborating with technical and non-technical stakeholders.
Advantages:
- Basic understanding of AI/ML concepts such as training, inference, data preprocessing, and model evaluation.
- Experience testing AI models and ensuring their reliability under diverse data inputs is a plus.
- Knowledge of computer vision, image, or audio processing.
- Experience working in AI-focused companies.
- Experience with testing cloud/data center applications.