Department: Platform Engineering
Qualification: B.Tech / B.E. / B.Sc. in Computer Science, Information Technology, or a related discipline
Experience: Freshers (2026 & 2025 Graduates only)
Work Location: Bangalore (Sattva Global City)
Work Model: Work from Office
About Aura Cloud
Aura Cloud delivers a next-generation cloud-native and cloud-agnostic core banking platform designed for innovation in financial services. With an API-first approach, the Aura platform offers a wide range of modules including Loans, Deposits, Cards, Payments, and more, supporting multi-currency and multi-entity setups for global scalability. The platform ensures operational efficiency, fast implementation, and seamless integration with over 2,000 APIs. Recognized for its robust and flexible architecture, Aura is ISO 27001 and ISO 9001 certified, making it a trusted choice for financial institutions seeking to grow and streamline their business.
Role Overview
We are looking for a curious, analytical, and AI-oriented Evaluation Engineer Intern to help validate and evaluate platform features developed by our engineering teams. The role involves leveraging AI tools to design and build practical use cases, create evaluation scenarios, execute tests, and analyse results to assess the functionality, accuracy, reliability, and overall quality of platform features.
The ideal candidate should have a strong interest in AI-assisted development, software testing, problem-solving, and systematic evaluation of software products.
Key Responsibilities
- AI Evaluation Framework: Create AI-based frameworks for evaluation of both human and AI generated code
- AI-Assisted Use Case Development: Leverage AI tools to design and build use cases, test scenarios, and evaluation workflows for validating platform features.
- Feature Validation: Understand platform requirements and expected behaviour to develop relevant test cases and validate newly developed features.
- Evaluation & Analysis: Execute evaluation scenarios, analyse outputs, compare actual results against expected outcomes, and identify gaps or inconsistencies.
- AI Tool Utilisation: Use AI-powered tools to generate test scenarios, create test data, automate repetitive evaluation tasks, and improve testing efficiency.
- Defect Identification: Identify, document, and report functional issues, unexpected behaviour, edge cases, and deviations from expected results.
- Test Automation: Develop basic scripts and automated workflows, where applicable, to support repeatable and scalable feature evaluation.
- Documentation: Maintain clear documentation of use cases, evaluation criteria, test results, observations, and identified issues.
- Cross-Functional Collaboration: Work closely with Engineering, Product and Business Analysis teams to understand feature requirements and support continuous product improvement.
- Continuous Improvement: Explore new AI tools, evaluation techniques, and testing methodologies to improve the effectiveness and coverage of platform validation.
Required Skills & Qualifications
- B.Tech / B.E. / B.Sc. graduates (2026 & 2025 batches) in Computer Science, Information Technology, or a related discipline.
- Working knowledge of generative AI tools, Large Language Models (LLMs), and prompt engineering, backed by project(s) in GitHub
- Basic understanding of software development concepts, programming fundamentals, and software testing principles.
- Exposure to at least one programming or scripting language, preferably Python, JavaScript, Java, or a similar language.
- Strong analytical and logical reasoning skills, with an ability to identify patterns, inconsistencies, and potential failure scenarios.
- Good written and verbal communication skills, with attention to detail and a structured approach to documentation.
- Willingness to learn new technologies, explore AI-assisted workflows, and work in a fast-paced product development environment.
Preferred / Good-to-Have Skills
- Familiarity in using AI tools and techniques to develop use cases, generate test scenarios, and evaluate software outputs.
- Basic knowledge of test automation frameworks, debugging, and version control tools such as Git.
- Exposure to API testing, REST APIs, JSON, SQL, or database concepts.
- Basic understanding of functional testing, regression testing, edge-case testing, and test-driven approaches.
Key Competencies
- Ability to translate requirements into practical evaluation scenarios and use cases.
- Analytical thinking and structured problem-solving.
- Attention to detail and a quality-first mindset.
- Adaptability, ownership, and eagerness to learn.
- Collaboration and effective communication.
Learning & Growth Opportunities
- Hands-on experience in AI-assisted software development and platform evaluation.
- Exposure to real-world product engineering, software quality, and automated testing practices.
- Opportunity to work with cross-functional teams and contribute to the validation of production-oriented platform features.
- Practical experience in building reusable evaluation use cases and improving software quality through AI-driven approaches.
