Hiring: Agentic AI Engineer (LangGraph, LangChain, Python & Golang)// Remote100%

We are seeking an experienced Agentic AI Engineer to design, develop, and deploy next-generation AI agents and autonomous systems. The ideal candidate will have strong expertise in LangGraph, LangChain, Python, Golang, LLMs, RAG architectures, and AI agent orchestration frameworks.

Key Responsibilities:

✅ Design and develop autonomous AI agents using LangGraph and LangChain

✅ Build multi-agent systems capable of planning, reasoning, tool usage, and workflow orchestration

✅ Develop scalable backend services using Python and Golang

✅ Integrate Large Language Models (OpenAI, Claude, Gemini, Llama, etc.) into enterprise applications

✅ Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases

✅ Develop APIs and microservices for AI-powered applications

✅ Build agent memory, tool-calling, and workflow automation capabilities

✅ Optimize prompt engineering, model performance, latency, and cost efficiency

✅ Collaborate with product managers, architects, and stakeholders to deliver AI solutions

✅ Ensure AI governance, security, and scalability best practices

Required Skills:

✔ Strong experience with Python and Golang

✔ Hands-on expertise with LangChain and LangGraph

✔ Experience building AI Agents, Multi-Agent Systems, and Agentic Workflows

✔ Strong understanding of LLMs, Prompt Engineering, and Fine-Tuning concepts

✔ Experience with RAG, Embeddings, Vector Databases (Pinecone, Weaviate, Chroma, FAISS)

✔ Experience with REST APIs, FastAPI, Flask, or Gin Framework

✔ Strong knowledge of Microservices Architecture

✔ Experience with Docker, Kubernetes, and Cloud Platforms (AWS, Azure, or Google Cloud Platform)

✔ Knowledge of MCP (Model Context Protocol), Tool Calling, Function Calling, and AI Workflow Orchestration

✔ Experience with Git, CI/CD, and Agile/Scrum methodologies

Preferred Qualifications:

➕ Experience with OpenAI, Anthropic Claude, Gemini, Llama, and Hugging Face models

➕ Experience with Graph Databases (Neo4j)

➕ Knowledge of AI Observability and Monitoring tools

➕ Experience with Event-Driven Architecture and Distributed Systems

➕ Exposure to MLOps and LLMOps practices