• Design and develop AI-driven agents for customer service, process automation, and knowledge retrieval. • Implement LLMs (Large Language Models) and NLP techniques to improve AI agent capabilities. • Optimize prompt engineering and retrieval-augmented generation (RAG) techniques for efficiency and accuracy. • Integrate AI models with APIs, cloud services, and existing enterprise systems. • Fine-tune AI models and continuously improve their context awareness and problem-solving capabilities. • Work with vector databases, embeddings, and knowledge graphs for AI memory and reasoning. • Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to deploy AI-driven solutions. • Monitor and improve AI performance using A/B testing, feedback loops, and real-world user interactions.