AI-Native Tester :

We are seeking an AI-Native Tester with strong software testing fundamentals, hands-on API testing experience, and working knowledge of ETL and data validation concepts. The ideal candidate should be comfortable testing AI-enabled applications, validating APIs, working with data flows, and using automation and AI-assisted techniques to improve quality and speed of delivery.

Key Responsibilities:

- Design and execute test scenarios for AI-enabled applications, AI agents, copilots, chat-based experiences, and AI-assisted workflows.
- Validate AI outputs for accuracy, relevance, groundedness, consistency, hallucination risk, and responsible AI considerations.
- Create prompt-based test scenarios, reusable evaluation datasets, and regression packs for AI and GenAI use cases.
- Perform functional, integration, regression, exploratory, defect validation, and end-to-end business process testing.
- Design and execute API test cases for REST/SOAP services, including request and response validation, schema validation, error handling, and negative scenarios.
- Use tools such as Postman, Swagger/OpenAPI, REST Assured, or Playwright API testing for API validation and automation.
- Validate basic ETL and data flow scenarios including source-to-target mapping, transformation logic, reconciliations, row counts, duplicates, and data quality checks.
- Write SQL queries to support data validation, reporting checks, and issue analysis across source, staging,



and target layers.
- Develop and maintain automation scripts for UI, API, and data validation using Playwright, Python, TypeScript, or similar tools.
- Collaborate with product owners, developers, data engineers, AI engineers, and business stakeholders to clarify requirements and drive quality early in the lifecycle.
- Log, track, and retest defects using tools such as JIRA, Azure DevOps, ALM, or equivalent defect management platforms.
- Support CI/CD, shift-left testing, and continuous improvement by identifying opportunities to use AI and automation accelerators.

Preferred Skills:

- Exposure to AI evaluation frameworks such as prompt evaluation, RAG evaluation, LLM benchmarking, or human feedback-based evaluation.
- Basic understanding of RAG, embeddings, vector search, knowledge retrieval, and agentic workflows.
- Knowledge of cloud platforms such as Azure and DevOps practices.
- Experience in test data creation, synthetic data generation, or data quality automation.
- Ability to use AI tools responsibly to accelerate requirement analysis, test design, automation, and defect analysis.

Education / Skilled Qualifications:

- Bachelors or Master’s degree in Computer Science, Information Technology, Engineering, or a related discipline.
- Relevant certifications in software testing, automation, cloud, data engineering, or AI/GenAI testing will be an added advantage.

📌 AI-Native Testing (Bengaluru)
🏢 KPMG India
📍 Bengaluru