- Design, develop, and deploy enterprise-scale Generative AI applications using Large Language Models (LLMs).
- Develop AI-powered assistants, copilots, document intelligence systems, and workflow automation solutions.
- Build production-ready GenAI applications leveraging AWS Bedrock and foundation models.
- Implement model orchestration frameworks for complex reasoning and task execution.
- Design AI systems capable of handling structured and unstructured enterprise data.
- Design and implement intelligent Multi-Agent Systems using LangGraph, LangChain, CrewAI, or similar frameworks.
- Develop autonomous AI agents capable of task planning, execution, reasoning,
and collaboration.
- Build agent orchestration frameworks for business process automation.
- Build scalable data ingestion pipelines for structured, semi-structured, and unstructured data sources.
- Develop ETL workflows using Python and PySpark for large-scale document processing.
- Process PDFs, Word documents, emails, websites, and enterprise knowledge repositories.
- Design advanced prompt engineering strategies for business-specific use cases.
- Develop prompt templates and reusable prompt libraries.
- Perform prompt tuning and contextual optimization.