Senior Software -AI Automation Engineer
Coralai · Bengaluru · onsite · Posted 29d ago
Undisclosed9–12 yrsfulltimeSourced from
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About this role
Education Qualification : Any graduation or related field or higher with minimum 3 years of Relevant experience.
Position Description:
We are seeking an Automation Quality Engineer with strong hands-on experience in Java and/or Python automation frameworks and practical exposure to AI-driven testing. The ideal candidate will play a key role in validating intelligent applications, ensuring the quality, reliability, and performance of AI-enabled systems. This role involves testing across traditional automation frameworks as well as advanced AI workflows, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Vector Databases, and OpenAI APIs.
Position Description:
We are seeking an Automation Quality Engineer with strong hands-on experience in Java and/or Python automation frameworks and practical exposure to AI-driven testing. The ideal candidate will play a key role in validating intelligent applications, ensuring the quality, reliability, and performance of AI-enabled systems. This role involves testing across traditional automation frameworks as well as advanced AI workflows, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Vector Databases, and OpenAI APIs.
Your future duties and responsibilities:
Design, develop, and maintain automation test frameworks using Java and/or Python.
Implement UI, API, and backend automation using tools such as Selenium, Playwright, REST Assured, PyTest, or similar.
Validate LLM-based applications, ensuring prompt accuracy, response quality, hallucination detection, and consistency.
Test and evaluate RAG pipelines, including document ingestion, embeddings, retrieval accuracy, and response relevance.
Work with Vector Databases (FAISS, Pinecone, Chroma, Weaviate) to validate indexing, retrieval, and performance.
Integrate and test applications using OpenAI APIs or similar LLM providers.
Leverage LangChain (or equivalent frameworks) for testing chains, agents, tools, and workflows.
Create automated test cases for AI workflows, model outputs, prompt versions, and inference pipelines.
Implement data-driven and AI-assisted testing strategies.
Collaborate with Data Scientists, Developers, and Product teams to define quality metrics for AI systems.
Participate in CI/CD pipelines to enable continuous testing and enforce quality gates.
Ensure compliance with security, performance, and scalability standards.
Implement UI, API, and backend automation using tools such as Selenium, Playwright, REST Assured, PyTest, or similar.
Validate LLM-based applications, ensuring prompt accuracy, response quality, hallucination detection, and consistency.
Test and evaluate RAG pipelines, including document ingestion, embeddings, retrieval accuracy, and response relevance.
Work with Vector Databases (FAISS, Pinecone, Chroma, Weaviate) to validate indexing, retrieval, and performance.
Integrate and test applications using OpenAI APIs or similar LLM providers.
Leverage LangChain (or equivalent frameworks) for testing chains, agents, tools, and workflows.
Create automated test cases for AI workflows, model outputs, prompt versions, and inference pipelines.
Implement data-driven and AI-assisted testing strategies.
Collaborate with Data Scientists, Developers, and Product teams to define quality metrics for AI systems.
Participate in CI/CD pipelines to enable continuous testing and enforce quality gates.
Ensure compliance with security, performance, and scalability standards.
Required qualifications to be successful in this role:
Strong programming skills in Python.
Hands-on experience with automation testing frameworks (Selenium, Playwright, REST Assured, PyTest, etc.).
Practical experience with LLMs (OpenAI GPT, Azure OpenAI, or similar).
Solid understanding and exposure to RAG architectures.
Experience working with Vector Databases for embeddings and semantic search.
Hands-on usage of OpenAI APIs (chat/completions, embeddings, etc.).
Experience with LangChain for prompt chaining, memory, and tool usage.
Strong knowledge of API testing, SQL, and data validation.
Familiarity with CI/CD tools (Jenkins, GitHub Actions, Azure DevOps).
Good understanding of SDLC, STLC, and Agile methodologies.
Good-to-Have Skills
Certification in LLMs and/or Python.
Exposure to AI-assisted testing strategies and emerging AI QA tools.
Experience with performance testing of AI-enabled systems.
Knowledge of cloud-based AI platforms and orchestration frameworks
Hands-on experience with automation testing frameworks (Selenium, Playwright, REST Assured, PyTest, etc.).
Practical experience with LLMs (OpenAI GPT, Azure OpenAI, or similar).
Solid understanding and exposure to RAG architectures.
Experience working with Vector Databases for embeddings and semantic search.
Hands-on usage of OpenAI APIs (chat/completions, embeddings, etc.).
Experience with LangChain for prompt chaining, memory, and tool usage.
Strong knowledge of API testing, SQL, and data validation.
Familiarity with CI/CD tools (Jenkins, GitHub Actions, Azure DevOps).
Good understanding of SDLC, STLC, and Agile methodologies.
Good-to-Have Skills
Certification in LLMs and/or Python.
Exposure to AI-assisted testing strategies and emerging AI QA tools.
Experience with performance testing of AI-enabled systems.
Knowledge of cloud-based AI platforms and orchestration frameworks
Skills:
- Java
- Large Language Model (LLM)
- OpenAI
- Python
- Selenium
Sourced from naukri
Skills
Quality EngineerSDLCQAAutomationJenkinsDevopsGithubAgileTesting FrameworksPerformance Testingai automationProgrammingLarge Language Models (LLMs)uiPythonSQLJavaAPI TestingAutomation TestingSeleniumcomplianceMicrosoft AzureArtificial Intelligence