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hace 1 mes

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**Req ID**: We are currently seeking a Data Prompt Engineer to join our team in Guadalajara, México (MX-MEX), Mexico (MX).- summarization) ensuring accuracy, consistency, and contextually appropriate outputs.- Context Engineering: Build and manage systems that provide the AI with the right information and tools at the right time. This includes selecting and structuring relevant data (user history, retrieved documents, external knowledge bases, etc.) to enhance the LLM's understanding and performance.- Testing and Quality Assurance: Develop and implement testing frameworks to evaluate prompt effectiveness, identify edge cases, and ensure consistent AI system performance, according to the LangChain Blog.- Performance Analysis and Improvement: Analyze AI system outputs and user feedback to identify patterns and areas for improvement, implementing data-driven refinements to prompts and context systems.- Documentation and Knowledge Sharing: Create and maintain comprehensive documentation of prompt design patterns, strategies, and best practices. Develop and maintain prompt libraries or repositories for reuse and knowledge sharing across the organization.- Ethical AI Use: Design prompts that minimize biases, respect data privacy, and promote transparency, adhering to ethical AI standards and regulations.- Stay Up-to-Date: Keep abreast of the latest advancements in AI, machine learning, generative AI, and prompt engineering techniques.**Required Skills**:- Overall 5+ years of experience- Bachelor's degree in computer science, Linguistics, Computational Linguistics, AI, Machine Learning, Data Science, or a related field, or equivalent experience.Preferred Skills:- LLM Expertise: Deep understanding of Large Language Model (LLM) capabilities, limitations, and optimal interaction patterns, including familiarity with different LLM architectures and prompting techniques.- Prompt Engineering Expertise: Advanced proficiency in crafting, testing, and refining prompts to produce consistent, accurate, and appropriate AI outputs.- Technical Understanding: Sufficient technical knowledge to collaborate effectively with AI engineers and operations specialists on prompt implementation, optimization, and troubleshooting.- Programming Skills: Proficiency in Python is highly beneficial, as it is widely used in AI development and for scripting, automation, and interacting with AI models.- Analytical Skills: Strong analytical capabilities to evaluate prompt performance data, identify patterns in AI responses, and implement data-driven improvements.- Creativity and Problem-Solving: Ability to think creatively**About NTT DATA