AI/LLM Prompt Engineer and Knowledge Retrieval Developer
Designed and implemented prompt engineering and function calling for large language models to enable intelligent AI agent responses. Conducted AI-assisted chart generation and automated insight delivery across energy sector datasets using integrated LLMs and knowledge retrieval systems. Developed RAG (Retrieval Augmented Generation) systems with Pinecone for multi-project support and orchestrated workflow automation with n8n and cloud APIs. • Integrated OpenAI, Anthropic, Google GenAI, and Groq for prompt response evaluation and text generation • Engineered prompt templates, scenarios, and test data for AI model validation • Utilized internal/proprietary tools and Azure for automation and function calling • Supported projects in the energy domain, leveraging vector databases for retrieval tasks