Performance Tester

As a Performance Test Engineer specializing in Generative AI, your role will involve ensuring scalability, reliability, and optimal performance of AI-powered applications, particularly those utilizing Large Language Models (LLM) and Generative AI (GenAI) technologies. Your responsibilities will include defining performance testing strategies, identifying bottlenecks, designing and executing various performance tests, monitoring system performance, and collaborating with cross-functional teams to optimize model serving and API performance. Key Responsibilities: - Define and implement performance testing strategies for GenAI and LLM-based applications. - Identify performance bottlenecks across APIs, model inference layers, vector databases, and cloud infrastructure. - Design, develop, and execute load, stress, spike, endurance, and scalability tests for GenAI applications. - Develop automated performance test scripts using tools like JMeter, LoadRunner, k6, or Gatling. - Collaborate with AI engineers, data scientists, DevOps, and architects to optimize model serving and API performance. - Document performance test results, bottlenecks, and optimization recommendations. Key Requirements: - 5+ years of experience in Performance Testing and Engineering. - Hands-on experience in performance testing GenAI / LLM-based applications. - Experience working with LLM platforms such as OpenAI GPT models, Gemini, Llama 2, Claude, or Grok. - Proficiency in performance testing tools such as JMeter, LoadRunner, k6, or Gatling. - Understanding of CI/CD pipelines and DevOps practices. - Bachelor's degree in Computer Science, Information Technology, or related field. - Strong analytical and troubleshooting skills. - Excellent communication and stakeholder management skills. *Note: The additional details of the company were not provided in the Job Description. As a Performance Test Engineer specializing in Generative AI, your role will involve ensuring scalability, reliability, and optimal performance of AI-powered applications, particularly those utilizing Large Language Models (LLM) and Generative AI (GenAI) technologies. Your responsibilities will include defining performance testing strategies, identifying bottlenecks, designing and executing various performance tests, monitoring system performance, and collaborating with cross-functional teams to optimize model serving and API performance. Key Responsibilities: - Define and implement performance testing strategies for GenAI and LLM-based applications. - Identify performance bottlenecks across APIs, model inference layers, vector databases, and cloud infrastructure. - Design, develop, and execute load, stress, spike, endurance, and scalability tests for GenAI applications. - Develop automated performance test scripts using tools like JMeter, LoadRunner, k6, or Gatling. - Collaborate with AI engineers, data scientists, DevOps, and architects to optimize model serving and API performance. - Document performance test results, bottlenecks, and optimization recommendations. Key Requirements: - 5+ years of experience in Performance Testing and Engineering. - Hands-on experience in performance testing GenAI / LLM-based applications. - Experience working with LLM platforms such as OpenAI GPT models, Gemini, Llama 2, Claude, or Grok. - Proficiency in performance testing tools such as JMeter, LoadRunner, k6, or Gatling. - Understanding of CI/CD pipelines and DevOps practices. - Bachelor's degree in Computer Science, Information Technology, or related field. - Strong analytical and troubleshooting skills. - Excellent communication and stakeholder management skills. *Note: The additional details of the company were not provided in the Job Description.