Description
We are building a production-grade AI agent system that will operate as a core automation layer across multiple internal business workflows and external integrations. This is not a prototype or chatbot-style implementation. The focus is on building reliable, stateful, tool-using agents that can execute multi-step tasks, interact with APIs, maintain context, and operate with minimal supervision in real business environments. Project Scope The system will include multiple specialized agents, each responsible for different operational domains such as: - Data processing and enrichment pipelines - API orchestration across third-party services (CRM, email, analytics, internal databases) - Automated decision-making workflows with guardrails and validation layers - Retrieval-augmented generation (RAG) over structured and unstructured data - Task execution with retry logic, logging, and audit trails - Human-in-the-loop approval flows for sensitive operations Core Requirements We are looking for someone with deep experience in: - Python backend development (FastAPI or similar frameworks) - LLM integration (OpenAI, Anthropic, or equivalent APIs) - Agent frameworks (LangChain, LangGraph, CrewAI, or custom implementations) - Tool calling / function calling architectures - Workflow orchestration and queue systems (Redis, Celery, or similar) - Database design for stateful agent memory (PostgreSQL, vector databases) - API integrations (REST, GraphQL, OAuth-based systems) What You Will Be Bui