Вакансии: QA & Test Automation — Израиль

Develop network simulation applications and automated tests to verify networking software for high-performance computing and AI workloads. Collaborate with software, firmware, and architecture teams to improve test coverage and product quality.

Own end-to-end quality across web and mobile applications, backend services, integrations, tracking systems and data flows. Lead the QA team while remaining approximately 70% hands-on.

Join a VLSI chip validation team testing networking switch designs after tape-out. Develop Python-based automation, run system-level tests, investigate failures, and collaborate with architecture, design, and pre-silicon validation teams.

Join a software engineering team working on SONiC Network OS products. Design and maintain automated test suites and collaborate with development and architecture teams.

Lead integration validation for a next-generation machine-learning accelerator platform. Own the test infrastructure and system-level checks that help ensure software, firmware, and hardware components are ready for production.

Build an intelligent testing ecosystem for a large-scale AI data platform. Develop autonomous tools that validate software, detect regressions, and test distributed systems.

Join an engineering team developing AI-powered tools and automated test workflows for system-level validation in 5G and embedded systems. The role requires at least three days per week in the office.

Lead and govern testing for a large-scale SAP S/4HANA transformation program in the defense sector. The role is fully on site at the customer's premises and involves close coordination across business, functional, technical, and infrastructure teams.

Lead system testing for networking software and systems, improving product quality through test planning, coverage, production test flows, and quality monitoring.

Own software quality from requirements review through release validation, helping deliver stable, secure, and reliable products. Work closely with developers, product managers, and DevOps, using AI-assisted tools to improve testing and defect analysis.