• Develop and refine effective prompts for various AI use cases (e.g., data analysis, report generation, survey development, synthetic data generation). • Iterate rapidly on prompt design and development strategies to improve model performance, accuracy, efficiency, and reduce latency. • Collaborate with the AI Native team to experiment with and deploy state-of-the-art LLM-enabled systems. • Contribute to production code and participate in code reviews. • Implement features like RAG, few-shot prompting, and domain-specific fine-tuning. • Develop and execute evaluation plans to measure the performance of LLMs. • Gather user feedback, interpret results, and iteratively enhance model outputs and user experience. • Partner with product managers and stakeholders to translate customer use-cases and requirements into LLM-enabled solutions. • Coordinate with other developers to ensure seamless integration of AI models into applications and services. In many cases, you will own implementation end-to-end.