Shure

Software Testing Intern

HyderabadInternshipPosted 2 days ago

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Join Shure's quality assurance team as a software testing intern, contributing to the validation and verification of software products across development cycles.
Participate in designing and executing test cases, identifying defects, and documenting findings through formal defect-tracking tools.
Support test automation initiatives by writing and maintaining automated test scripts using industry-standard frameworks and tools.
Work with APIs and databases, including writing and validating SQL queries to ensure data integrity and system correctness.
Collaborate with developers and QA engineers to analyze end-to-end system behavior and troubleshoot issues using logical problem-solving.
Engage with emerging AI technologies by testing features involving large language models, generative AI, and agentic AI systems, including validation of outputs and risk assessment.

Currently enrolled in or recently graduated from a Bachelor's or Master's degree programme in Computer Science, IT, Software Engineering, AI, Data Science, or related discipline.
Solid grasp of software development lifecycle (SDLC), software testing lifecycle (STLC), debugging methodologies, and core testing principles.
Hands-on experience with at least one programming or scripting language such as Python, Java, JavaScript, TypeScript, or equivalent.
Familiarity with test automation concepts, API testing approaches, relational databases, SQL fundamentals, version control systems, and defect-tracking workflows.
Knowledge of LLMs, generative AI models, and agentic AI, including their practical applications in QA and software engineering contexts.
Demonstrated ability to learn new tools and technologies rapidly, think critically about system problems, and communicate technical observations in clear terms.
Keen eye for detail, strong ownership mindset, intrinsic curiosity, and genuine enthusiasm for experimenting with new methodologies.

Practical experience with continuous integration and continuous deployment (CI/CD) platforms such as Jenkins, including understanding of pipelines, build logs, and automated quality checks.
Working knowledge of Git-based version control and collaboration platforms including GitHub, GitLab, or Azure DevOps.
Exposure to prompt engineering, retrieval-augmented generation (RAG), tool or function calling patterns, or AI-agent frameworks.
Understanding of responsible and ethical AI principles, encompassing data privacy, security controls, hallucination mitigation, output validation mechanisms, and human-in-the-loop review processes.