F2F Interview || Python FSD with AI Agents

Role: Integration Engineer: Full stack Python (AI Agents, LangGraph, Context Engineering) Location: 1st Atlanta, 2nd Dallas, 3rd Seattle (Onsite no remote) Key Responsibilities 1. AI Agent Development • Build and deploy AI-powered agents for automation, data processing, decision-making, and conversational workflows. • Implement multi-agent collaboration where different agents handle different tasks and communicate with each other. 1. LangGraph Integration • Use LangGraph (a framework similar to LangChain) to design and orchestrate complex AI workflows. • Create graph-based flows for reasoning, context management, and decision-making within AI systems. 1. Context Engineering • Design and optimize how AI systems understand and manage context, such as: • Memory handling (short-term and long-term context) • Retrieval-augmented generation (RAG) • Knowledge graph integration • Improve accuracy and relevance of AI model responses by structuring prompts and data pipelines. 1. Full-Stack Python Development • Backend: Build scalable APIs, microservices, and AI inference pipelines using Python frameworks (FastAPI, Flask, Django). • Frontend (optional but preferred): Develop dashboards or tools for interacting with AI agents, possibly using React or similar frameworks. • Manage deployment on cloud platforms (AWS, GCP, Azure). 1. Integration & Automation • Integrate AI workflows with existing enterprise systems such as CRMs, ERPs, or custom applications. • Create automation scripts and pipelines to handle real-time data ingestion and model updates.