· Develop agentic AI workflows using LangChain/LangGraph with custom tools, memory, decision logic, and MCP integrations.
· Implement LLM applications with advanced prompt engineering (structured outputs, function calling, context management) and build RAG pipelines with vector databases.
· Build and deploy event-driven AI services on AWS using Bedrock, SageMaker, Lambda, EventBridge, Step Functions, API Gateway, DynamoDB, and S3.
· Write clean, testable Python code; create unit/integration tests; and package solutions with CI/CD pipelines (GitHub Actions).
· Monitor and optimize AI application performance through logging, metrics, token usage, and cost management.
· Integrate AI services with APIs, backend systems, and databases to ensure secure and reliable data flow.
· Contribute to document AI and predictive analytics models for information extraction, classification, and forecasting.
· Fine-tune Hugging Face Transformer models (BERT, RoBERTa, LayoutLM, DistilBERT) and train neural networks (PyTorch/TensorFlow) for supervised tasks.
· Implement data preprocessing and annotation workflows for training and evaluation.
· Work with OCR and text-processing tools (AWS Textract, Tesseract) for semi-structured/unstructured documents.