Gen AI - SDET
Barclays · Pune · Posted 2026-07-18
Tech stack: AWS, Azure, Docker, Jenkins, Kubernetes, Python
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About the role
To design, develop, and execute testing strategies to validate functionality, performance, and user experience, while collaborating with cross-functional teams to identify and resolve defects, and continuously improve testing processes and methodologies, to ensure software quality and reliability.
Responsibilities:
- Development and implementation of comprehensive test plans and strategies to validate software functionality and ensure compliance with established quality standards.
- Creation and execution automated test scripts, leveraging testing frameworks and tools to facilitate early detection of defects and quality issues. .
- Collaboration with cross-functional teams to analyse requirements, participate in design discussions, and contribute to the development of acceptance criteria, ensuring a thorough understanding of the software being tested.
- Root cause analysis for identified defects, working closely with developers to provide detailed information and support defect resolution.
- Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing.
- Stay informed of industry technology trends and innovations, and actively contribute to the organization's technology communities to foster a culture of technical excellence and growth.
Qualifications:
- Expert-level proficiency in Large Language Models (LLM), LangChain, and LangGraph frameworks
- Advanced Python programming skills with demonstrated ability to architect scalable test automation solutions
- Deep hands-on experience with Generative AI and Agentic AI implementations in production environments
- Strong background in:
- Generative AI architecture and evaluation methodologies
- Machine Learning model testing and validation
- Natural Language Understanding (NLU) testing strategies
- Natural Language Processing (NLP) quality assurance
- Comprehensive knowledge of AWS services, particularly Bedrock, Lambda and CloudWatch
- Experience architecting and implementing enterprise-scale cloud-based testing solutions
- Expert proficiency with version control systems (Git, Stash) and branching strategies
- Proven experience designing and optimizing CI/CD pipelines using Jenkins, GitLab CI, or similar tools
- Deep understanding of Agile/Scrum methodology, SDLC best practices, and DevOps culture
- Demonstrated ability to drive quality initiatives and establish testing excellence across organizations
- Proven expertise in leading cross-functional collaboration with development, product, and operations teams
- Experience establishing quality gates and governance frameworks for Gen AI applications
- Expert-level knowledge in UI, mobile, and API testing methodologies
- Advanced proficiency with Behavior-Driven Development (BDD) frameworks and test design patterns
- Experience with test management and reporting tools including Jira, Xray, ALM, and TestRail
- Knowledge of prompt engineering and LLM evaluation frameworks (RAGAS, DeepEval, etc.)
- Familiarity with vector databases for RAG testing
- Experience with performance and load testing of Gen AI applications
- Understanding of AI ethics, bias detection, and responsible AI testing practices
- Certifications in AWS, Azure AI, or relevant testing frameworks
- Experience with containerization (Docker, Kubernetes) for test environments
- Background in data engineering or data quality testing
- You may be assessed on key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen, strategic thinking and digital and technology, as well as job-specific technical skills.
- This role is based out of Pune.
Qualifications
- Expert-level proficiency in Large Language Models (LLM), LangChain, and LangGraph frameworks
- Advanced Python programming skills with demonstrated ability to architect scalable test automation solutions
- Deep hands-on experience with Generative AI and Agentic AI implementations in production environments
- Strong background in:
- Generative AI architecture and evaluation methodologies
- Machine Learning model testing and validation
- Natural Language Understanding (NLU) testing strategies
- Natural Language Processing (NLP) quality assurance
- Comprehensive knowledge of AWS services, particularly Bedrock, Lambda and CloudWatch
- Experience architecting and implementing enterprise-scale cloud-based testing solutions
- Expert proficiency with version control systems (Git, Stash) and branching strategies
- Proven experience designing and optimizing CI/CD pipelines using Jenkins, GitLab CI, or similar tools
- Deep understanding of Agile/Scrum methodology, SDLC best practices, and DevOps culture
- Demonstrated ability to drive quality initiatives and establish testing excellence across organizations
- Proven expertise in leading cross-functional collaboration with development, product, and operations teams
- Experience establishing quality gates and governance frameworks for Gen AI applications
- Expert-level knowledge in UI, mobile, and API testing methodologies
- Advanced proficiency with Behavior-Driven Development (BDD) frameworks and test design patterns
- Experience with test management and reporting tools including Jira, Xray, ALM, and TestRail
- Knowledge of prompt engineering and LLM evaluation frameworks (RAGAS, DeepEval, etc.)
- Familiarity with vector databases for RAG testing
- Experience with performance and load testing of Gen AI applications
- Understanding of AI ethics, bias detection, and responsible AI testing practices
- Certifications in AWS, Azure AI, or relevant testing frameworks
- Experience with containerization (Docker, Kubernetes) for test environments
- Background in data engineering or data quality testing
- You may be assessed on key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen, strategic thinking and digital and technology, as well as job-specific technical skills.
- This role is based out of Pune.
Responsibilities
- Development and implementation of comprehensive test plans and strategies to validate software functionality and ensure compliance with established quality standards.
- Creation and execution automated test scripts, leveraging testing frameworks and tools to facilitate early detection of defects and quality issues..
- Collaboration with cross-functional teams to
- analyse requirements, participate in design discussions, and contribute to the development of acceptance criteria, ensuring a thorough understanding of the software being tested.
- Root cause analysis for identified defects, working closely with developers to provide detailed information and support defect resolution.
- Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing.
- Stay informed of industry technology trends and innovations, and actively contribute to the organization's technology communities to foster a culture of technical excellence and growth.