- Design and develop Generative AI solutions using Large Language Models (LLMs).
- Fine-tune, customize, and optimize foundation models for domain-specific use cases.
- Build and deploy NLP and conversational AI applications such as chatbots, virtual assistants, and document intelligence systems.
- Develop RAG (Retrieval Augmented Generation) pipelines using vector databases.
- Work with AWS SageMaker for model training, deployment, monitoring, and MLOps workflows.
- Implement prompt engineering strategies to improve model performance and output quality.
- Evaluate and optimize model accuracy, latency, scalability, and cost.
- Integrate AI services with enterprise applications through APIs and microservices.
- Collaborate with data scientists, software engineers, and business stakeholders to deliver AI-driven solutions.
- Stay updated with advancements in Generative AI, LLMs, and emerging AI technologies.