> Markdown version of [/jobs/ext/4008657-ai-agentic-tester](https://www.wearedevelopers.com/jobs/ext/4008657-ai-agentic-tester). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Agentic Tester - **Company:** TALENT Software Services - **Location:** Denver, CO, United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Python (Programming Language), OpenAI, Swagger, Selenium, Strategies of Testing, Postman, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Agentic-AI, Pytest, AI Platforms, Playwright, Virtual Agents, Google Gemini, Restful APIs, Api Management - **Published:** October 29, 2026 - **Apply:** https://www.thejobnetwork.com/job/efc1a79f-db72-4aa0-b0a0-16600ea43c2f/ai-agentic-tester ## About the Role Skills: QA/Test Engineering experience Must have- Experience testing Generative AI, LLM, or AI-based applications. Keyword: Skills: Modern Functional Quality Engineering Experience Required: 2-4 Years PFB the responsibilities and skills needed, * 3-8 years of QA/Test Engineering experience. * Experience testing Generative AI, LLM, or AI-based applications. * Knowledge of AI Agents, Agentic AI, RAG, and prompt engineering. * Hands-on experience with API testing (Postman, Swagger, REST APIs). * Experience with automation frameworks (Selenium, Playwright, PyTest). * Proficiency in Python. * Understanding of AI evaluation metrics and testing methodologies * Knowledge of Azure OpenAI, AWS Bedrock, Gemini, or similar AI platforms ## Description * Validate AI agent workflows against business requirements. * Test end-to-end AI use cases, including multi-agent interactions. * Verify task completion accuracy and output quality. * Test agent orchestration, tool calling, and workflow execution. AI Model Validation * Evaluate LLM responses for accuracy, relevance, and consistency. * Test prompt engineering effectiveness and response quality. * Validate Retrieval-Augmented Generation (RAG) outputs. * Measure hallucination rates and response reliability.