: Experience Range: 7-10 years

Job Location: Bangalore with Hybrid

Primary Skill

AI Validation & Testing

Chatbot & RAG Testing • LLM/Prompt Evaluation • Python Validation

AI Solution Testing: Validates AI-powered solutions including chatbots and generative AI features for accuracy, reliability, and edge cases

RAG Validation: Tests Retrieval-Augmented Generation pipelines for retrieval relevance, grounding, and hallucination handling

Agentic AI: Builds and tests agentic solutions such as MCP and prompting

Test Data & AI Evaluation

Data Quality • AI Eval Metrics • Responsible AI

Test Data Management: Curates and versions golden/evaluation datasets and validates data pipelines for integrity, completeness, and drift across training and inference

AI Evaluation: Hands-on with evaluation frameworks and metrics such as RAGAS, DeepEval, and LLM-as-judge, covering groundedness, relevance, and precision/recall

Responsible AI & Privacy: Bias and fairness checks, safety/guardrail, and PII/data-leakage validation

Languages & Frameworks

Python • Pytest

Core Languages: Proficient in Python for automation

Test Frameworks: Hands-on with Pytest, or equivalent

Framework Design: Build, scale, and maintain automation frameworks end-to-end

Secondary Skill

UI & API Testing

UI Automation • REST/GraphQL APIs • Contract Testing

UI Automation: End-to-end browser testing across modern web applications. Well versed with BDD frameworks like Cucumber/SpecFlow

API Testing: Validates REST/GraphQL APIs across microservices for correctness and edge cases

Cross-layer Coverage: Bridges UI and API layers for integrated test coverage

Tools: Experience with tools like Postman/Insomnia/Newman

Cloud, Infrastructure & CI/CD

AWS • SQL • CI/CD Pipelines

Cloud Exposure: Working knowledge of AWS/Azure services for test environments

SQL Proficiency: Uses SQL to query, validate, and debug data confidently

CI/CD Integration: Integrates test suites into Jenkins, GitHub Actions, GitLab CI, etc.

Profile description: Experience Range: 7-10 years

Job Location: Bangalore with Hybrid

Primary Skill

AI Validation & Testing





Chatbot & RAG Testing • LLM/Prompt Evaluation • Python Validation

AI Solution Testing: Validates AI-powered solutions including chatbots and generative AI features for accuracy, reliability, and edge cases

RAG Validation: Tests Retrieval-Augmented Generation pipelines for retrieval relevance, grounding, and hallucination handling

Agentic AI: Builds and tests agentic solutions such as MCP and prompting

Test Data & AI Evaluation

Data Quality • AI Eval Metrics • Responsible AI

Test Data Management: Curates and versions golden/evaluation datasets and validates data pipelines for integrity, completeness, and drift across training and inference

AI Evaluation: Hands-on with evaluation frameworks and metrics such as RAGAS, DeepEval, and LLM-as-judge, covering groundedness, relevance, and precision/recall

Responsible AI & Privacy: Bias and fairness checks, safety/guardrail, and PII/data-leakage validation

Languages & Frameworks

Python • Pytest

Core Languages: Proficient in Python for automation

Test Frameworks: Hands-on with Pytest, or equivalent

Framework Design: Build, scale, and maintain automation frameworks end-to-end

Secondary Skill

UI & API Testing

UI Automation • REST/GraphQL APIs • Contract Testing

UI Automation: End-to-end browser testing across up-to-date web applications. Well versed with BDD frameworks like Cucumber/SpecFlow

API Testing: Validates REST/GraphQL APIs across microservices for correctness and edge cases

Cross-layer Coverage: Bridges UI and API layers for integrated test coverage

Tools: Experience with tools like Postman/Insomnia/Newman

Cloud, Infrastructure & CI/CD

AWS • SQL • CI/CD Pipelines

Cloud Exposure: Working knowledge of AWS/Azure services for test environments

SQL Proficiency: Uses SQL to query, validate, and debug data confidently

CI/CD Integration:



Integrates test suites into Jenkins, GitHub Actions, GitLab CI, etc.

We offer: Experience Range: 7-10 years

Job Location: Bangalore with Hybrid

Primary Skill

AI Validation & Testing

Chatbot & RAG Testing • LLM/Prompt Evaluation • Python Validation

AI Solution Testing: Validates AI-powered solutions including chatbots and generative AI features for accuracy, reliability, and edge cases

RAG Validation: Tests Retrieval-Augmented Generation pipelines for retrieval relevance, grounding, and hallucination handling

Agentic AI: Builds and tests agentic solutions such as MCP and prompting

Test Data & AI Evaluation

Data Quality • AI Eval Metrics • Responsible AI

Test Data Management: Curates and versions golden/evaluation datasets and validates data pipelines for integrity, completeness, and drift across training and inference

AI Evaluation: Hands-on with evaluation frameworks and metrics such as RAGAS, DeepEval, and LLM-as-judge, covering groundedness, relevance, and precision/recall

Responsible AI & Privacy: Bias and fairness checks, safety/guardrail, and PII/data-leakage validation

Languages & Frameworks

Python • Pytest

Core Languages: Proficient in Python for automation

Test Frameworks: Hands-on with Pytest, or equivalent

Framework Design: Build, scale, and maintain automation frameworks end-to-end

Secondary Skill

UI & API Testing

UI Automation • REST/GraphQL APIs • Contract Testing

UI Automation: End-to-end browser testing across modern web applications. Well versed with BDD frameworks like Cucumber/SpecFlow

API Testing: Validates REST/GraphQL APIs across microservices for correctness and edge cases

Cross-layer Coverage: Bridges UI and API layers for integrated test coverage

Tools: Experience with tools like Postman/Insomnia/Newman

Cloud, Infrastructure & CI/CD

AWS • SQL • CI/CD Pipelines

Cloud Exposure: Working knowledge of AWS/Azure services for test environments

SQL Proficiency: Uses SQL to query, validate, and debug data confidently

CI/CD Integration: Integrates test suites into Jenkins, GitHub Actions, GitLab CI, etc.

📌 AI - AI/ML Engineer (Bengaluru)
🏢 Qualitest
📍 Bengaluru