Generative AI & Agentic AI

Project Scope: Design, develop, and implement AI-powered applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and workflow automation frameworks. Responsibilities include: •⁠ ⁠Developing AI agents capable of reasoning, tool calling, and multi-step workflow execution. •⁠ ⁠Building Retrieval-Augmented Generation (RAG) systems using vector databases and embedding models. •⁠ ⁠Integrating LLMs with external APIs, databases, and business applications. •⁠ ⁠Designing agent workflows using frameworks such as LangGraph, CrewAI, or similar agent orchestration platforms. •⁠ ⁠Developing backend services and APIs using Python and FastAPI. •⁠ ⁠Implementing memory, state management, and conversation workflows for AI assistants. •⁠ ⁠Building document processing, knowledge retrieval, and intelligent search solutions. •⁠ ⁠Creating evaluation, monitoring, and reliability mechanisms for AI systems. •⁠ ⁠Developing custom automation workflows and AI-powered business solutions. •⁠ ⁠Collaborating on architecture, implementation, testing, deployment, and optimization of AI applications. Deliverables: •⁠ ⁠Production-ready AI agent workflows. •⁠ ⁠RAG-based knowledge systems. •⁠ ⁠FastAPI backend services and integrations. •⁠ ⁠Documentation and technical implementation support. •⁠ ⁠Testing, debugging, and performance optimization of AI solutions. Required Skills: •⁠ ⁠Python •⁠ ⁠FastAPI •⁠ ⁠Large Language Models (LLMs) •⁠ ⁠Retrieval-Augmented Generation (RAG) •⁠ ⁠LangGraph / Agent Frameworks •⁠ ⁠Vector Databases •⁠ ⁠API Integration •⁠ ⁠PostgreSQL / Database Design •⁠ ⁠AI Workflow Automation