Python+ Agentic AI Engineer

1. Key Responsibilities

• Agent Development: Design, develop, and deploy autonomous AI agents that can break down tasks, reason, and act on goals.
• Tool Integration: Build custom tools (e.g., web search, calculators, database querying, APIs) that agents can call autonomously to solve complex problems.
• Workflow Orchestration: Develop and manage multi-agent workflows and pipelines to handle enterprise business logic.
• LLM Integration: Integrate Large Language Models (like OpenAI GPT, Claude, or Gemini) with backend enterprise infrastructure.
• RAG Implementation: Develop Retrieval-Augmented Generation (RAG) pipelines so agents can access proprietary, up-to-date knowledge bases.

2. Required Technical Skills.

• Core Languages: Advanced Python programming (including asynchronous programming for performance).
• AI Frameworks: Expertise in LangChain, LangGraph, and Microsoft AutoGen.
• Concepts: Deep understanding of Prompt Engineering, Agentic Loops, memory management, and function calling.
• Data & APIs: Experience connecting AI models to RESTful APIs, vector databases (e.g., Pinecone, Milvus), and relational databases.
• Deployment: Familiarity with deploying AI applications using Docker, Kubernetes, and cloud platforms (AWS, Azure, GCP).