

What you’ll be doing:
Review product requirements and develop test matrix.
Build testing-related documentation, including test plans, test approach, test cases and bug reports assessing quality and associated risks.
Manage bug lifecycle and co-work with inter-groups to work towards solutions.
Automate manual tests and assist in the architecture, building and implementing test frameworks.
Enhance the existing testing frameworks used in the organization by our engineers, including yourself, for areas such as UIs, REST APIs, process automation and performance validation.
Support a reliable fast feedback loop by integrating automation testing in CI and discovery pipelines.
What we need to see:
BS or higher degree or equivalent experience in Computer Science, Electronics or relatwed discipline with 5+ years QA experience.
Proficient with web based UI and RESTful APIs validation via code as well as Unix/Linux and shell/python programming skills.
Familiarity with networking protocols as well as working command of the Python programming language.
Rich experience in test cases development and failure root cause analysis.
Track record in identifying areas of process improvement
Good command of Cloud management systems and Kubernetes and supporting cloud infrastructure (Grafana etc)
Experience with building and handling CI/CD pipelines.
Hands-on experience working with Large Language Models (LLMs), including prompt engineering, fine-tuning, or integration into QA workflows
Fine-tuning or training models for QA-specific tasks - adapting LLMs or other models specifically for testing, documentation analysis, or requirement validation
Good QA sense including attention to detail, problem-solving, data analysis, quality standards knowledge, time management etc.
Excellent communicator, fluent written and verbal English.
Ways to stand out from the crowd:
Experience building AI systems such as RAG (Retrieval-Augmented Generation) pipelines, MRC (Machine Reading Comprehension) solutions, or AI agents
Building AI-powered test generation tools - using LLMs to automatically generate test cases, test code, edge cases, or synthetic test data
Experience working with NVIDIA GPU hardware is a strong plus
Scalability or performance testing knowledge is a plus
Experience with data analysis and system monitoring across distributed systems as well as experience with Golang
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