Python Developer (Exp-8 Y) with Agentic AI exp-Hybrid-Full Time

Key Skills: Python, Agentic AI, Generative AI, LLMs, LangChain, LangGraph, RAG, FastAPI, REST APIs, Vector Databases

Job Responsibilities

• Design, develop, and deploy Python-based applications incorporating Agentic AI and generative AI capabilities.

• Build AI agents capable of planning tasks, reasoning, selecting tools, and executing multi-step workflows with appropriate controls.

• Develop agentic workflows using frameworks such as LangGraph, LangChain, or similar technologies.

• Integrate Large Language Models (LLMs) from providers such as OpenAI, Azure OpenAI, or Anthropic into enterprise applications.

• Implement Retrieval-Augmented Generation (RAG) solutions using embeddings, vector databases, and semantic search.

• Develop REST APIs and backend services using FastAPI or Flask to expose AI agent capabilities to enterprise systems.

• Integrate AI agents with external APIs, databases, enterprise applications, and business tools to automate complex processes.

• Implement prompt engineering, context management, memory, and structured outputs to improve AI agent performance.

• Apply evaluation, logging, error handling, guardrails, and human-in-the-loop approvals to ensure reliable and responsible agent execution.

• Optimize application performance, scalability, latency, and LLM usage costs across AI-powered solutions.

• Collaborate with product owners, data scientists, and engineering teams to translate business requirements into production-ready AI solutions.

Required Skills

• 7 years of professional software development experience, with strong hands-on Python expertise.

• Practical experience building Agentic AI applications, autonomous or semi-autonomous agents, and multi-step workflows.

• Strong knowledge of LLMs, prompt engineering, RAG, embeddings, and vector search.

• Experience with LangGraph, LangChain, or comparable agent orchestration frameworks.

• Proficiency in FastAPI/Flask, REST APIs, asynchronous programming, and database integration.

• Familiarity with Git, Docker, CI/CD, cloud platforms, and production deployment practices.

• Strong analytical, debugging, communication, and problem-solving skills.