QA Engineer

Description

Job Summary: Velorum is seeking a QA Engineer to ensure the quality and reliability of the platform, validating knowledge extraction and error-free consumption of information. Key Highlights: 1. Knowledge Graph Validation 2. Conversational AI Testing 3. End-to-End Test Automation **Description:** ---------------- At **Velorum**, we are looking for a **QA Engineer** responsible for ensuring the quality and reliability of our platform. Their mission will be twofold: first, to validate that knowledge extraction from diverse sources (C\#, Java, SQL, Power BI) is processed correctly; and second, to ensure this information is consumed without errors across our suite of applications. **Key Responsibilities** * Knowledge Graph Validation: Ensure generation and enrichment algorithms accurately and coherently transform code and metadata into various graph elements. * Conversational AI Testing: Validate the accuracy of natural-language responses, verifying that delivered technical and functional information aligns with the actual graph. * Frontend Application Testing: Execute regression and usability tests on applications, ensuring visual consistency and navigation integrity. * Test Automation: Experience in implementing and architecting end-to-end tests. * Continuous Integration Automation: Collaborate with the DevOps team to integrate automated tests into continuous update pipelines for knowledge sources (GitHub, Bitbucket). **Requirements:** --------------- **Technical Requirements:** * Software Testing Experience: Minimum **5 years** in QA roles, preferably within SaaS platforms or data analytics tools. * Languages and Technologies: Proficiency in validating language processing workflows in C\#, Java, SQL, and BI tools such as Power BI. * Databases: Experience testing on SQL Server, Oracle, Snowflake, or Azure SQL. * Graph Knowledge (Preferred): Familiarity with graph structures and semantic modeling. * Automation Tools: Experience with frameworks such as Selenium, Cucumber, Playwright, Cypress, or API testing tools (REST/SOAP). * Environments: Familiarity with deployments on Kubernetes and Docker. **Soft Skills:** * Analytical Ability: Skill in understanding complex systems and uncovering non-obvious code dependencies or structures. * Attention to Detail: Critical for validating automatically generated technical and functional documentation. * Self-Management in Dynamic Environments: Ability to work autonomously in a rapidly evolving environment, taking initiative across processes and teams. * Communication: Ability to interact effectively with various team members, serving as a bridge to ensure functional requirements are met.