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Tier-1 brand and metro location raise competition, but niche GenAI expertise and seniority reduce applicant density.
LLM-focused QA skills are transferable but require niche AI testing expertise, giving moderate industry specificity.
Mandatory 8+ years plus required LLM/Agents testing, Selenium/Pytest and CI/CD indicate strict technical filters.
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Analyze business and technical specifications to define and execute functional and regression test cases for LLMs and AI-driven Agents.
Maintain and run automated tests using Selenium with Python and Pytest framework, including automation of web services using SoapUI and/or Python.
Design and perform validation for Large Language Models including prompt validation, accuracy checks, safety and ethical compliance, and adversarial testing (red teaming).
Minimum 8 years of software quality assurance testing experience.
Hands-on experience in LLM (Large Language Model) testing and Agents testing is highly preferred.
Experience with test automation tools: Selenium with Python, Pytest framework, SoapUI, Jira, Jenkins, Git, JMeter; familiarity with CI/CD pipelines required.
Basic understanding of AI and machine learning algorithms; knowledge of AI governance, bias detection, and safety validation is an advantage.
Experienced SQA professional specialized in testing AI technologies, especially LLMs and agent-based workflows, with a strong technical automation and scripting background.
Capable of working with multidisciplinary teams applying emerging AI technologies in financial services or similar regulated domains.
Able to perform complex validation including adversarial testing and safety compliance, using AI evaluation tools and frameworks like OpenAI Evals and Ragas.