Looking for Python Developer Lang Chain & Lang Graph _ Need local to CHARLOTTE NC _ Only locals required No Relocation_ PLEASE SHARE ONLY LOCAL TO CHARLOTTE NC. _In Person Interview

Role: Python Developer Lang Chain & Lang Graph

Client: Wells Fargo / Synechron

Location: CHARLOTTE NC (Day 1 Hybrid 3 days office in a week)

Face-2-Face interview round required with Client

Only locals required No Relocation

Need to Share live location at the time of submission.

Job Summary

We are looking for a skilled Python Developer with hands-on experience in Generative AI, Large Language Models (LLMs), LangChain, and LangGraph. The candidate will design, develop, and deploy AI-powered applications, intelligent agents, and Retrieval-Augmented Generation (RAG) solutions.

Key Responsibilities

• Develop scalable backend applications using Python, FastAPI, and REST APIs.
• Build LLM-powered applications using LangChain and LangGraph.
• Design and implement RAG pipelines using document loaders, text splitters, embeddings, and vector databases.
• Integrate LLMs such as OpenAI GPT, Azure OpenAI, Anthropic Claude, or open-source models.
• Develop AI agents with tool calling, function calling, and multi-step reasoning workflows.
• Implement stateful, multi-agent workflows using LangGraph, including conditional routing, persistence, checkpoints, and human-in-the-loop approval.
• Work with vector databases such as FAISS, Chroma, Pinecone, or Weaviate.
• Implement prompt engineering, structured outputs, and LLM response validation.
• Integrate external APIs, databases, and enterprise knowledge sources.
• Optimize latency, token consumption, reliability, and application performance.
• Write unit tests, debug applications, and follow secure coding practices.
• Deploy AI applications using Docker and cloud platforms such as AWS, Azure, or Google Cloud Platform.

Required Skills

• Strong programming skills in Python, including OOP, exception handling, asynchronous programming, and data structures.
• Hands-on experience with LangChain and LangGraph.
• Good understanding of LLMs, transformers, tokens, embeddings, and context windows.
• Practical experience building RAG applications and semantic search systems.
• Experience with REST APIs and FastAPI or Flask.
• Knowledge of vector databases and similarity search.
• Familiarity with SQL/NoSQL databases such as PostgreSQL, MySQL, or MongoDB.
• Experience with Git, debugging, testing, and software development best practices.

Preferred Skills

• Experience with multi-agent systems and agent orchestration.
• Knowledge of Model Context Protocol (MCP).
• Familiarity with LangSmith or similar LLM tracing and evaluation tools.
• Experience with AWS Bedrock, Azure AI, or Google Vertex AI.
• Knowledge of CI/CD, Docker, Kubernetes, and production monitoring.
• Understanding of LLM evaluation, guardrails, prompt injection risks, and responsible AI practices.

Education

Bachelor s or Master s degree in Computer Science, Information Technology, or a related field, or equivalent practical experience.