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

- **Company:** Visionary Innovative Technology Solutions LLC
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Application Performance Management, Microsoft Azure, Cloud Computing, Databases, Continuous Integration, Software Debugging, Python (Programming Language), OpenAI, Search Technologies, Software Deployment, Software Engineering, Data Logging, Enterprise Software Applications, LangChain, Retrieval-Augmented Generation, Flask (Web Framework), Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Backend, Agentic-AI, Git, Fastapi, Low Latency, Virtual Agents, Asynchronous Programming, Restful APIs, Docker, Web Api
- **Published:** October 30, 2026
- **Apply:** https://www.dice.com/job-detail/3da2cac2-1284-4492-a19e-093dbd6c98af

## About the Role

* 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.

## Description

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