Agentic AI Engineer

Design and develop advanced Applied AI solutions that integrate intelligent agents, large language models, and scalable data retrieval systems to deliver high-performance, production-ready AI applications.
Key Responsibilities
Develop and deploy agentic AI systems capable of autonomous reasoning and task execution.
Build RAG (Retrieval-Augmented Generation) pipelines to enhance LLM accuracy using structured and unstructured data sources.
Integrate and optimize Large Language Models (LLMs) for real-world enterprise use cases.
Design and maintain vector database architectures for semantic search and contextual retrieval.
Implement Model Context Protocol (MCP) integrations for efficient AI system communication.
Architect Agent-to-Agent (A2A) communication frameworks for multi-agent collaboration.
Create workflow orchestration pipelines using LangGraph for scalable AI process automation.
Ensure system performance, responsiveness, and reliability in production environments
Core Skills & Technologies
Agentic AI RAG Pipelines LLM Integration Vector Databases MCP A2A Architectures LangGraph AI System Design Semantic Search AI Orchestration