AI Engineer (Genai / Rag / Langgraph / Python)

Job Summary We are seeking a skilled AI Engineer with strong expertise in Generative AI, enterprise-grade Generative AI applications Prompt Engineering, Retrieval-Augmented Generation (RAG), LangGraph, Elastic Knowledge, and Python. You will build intelligent AI agents, optimize RAG pipelines, and integrate knowledge bases to deliver scalable AI solutions for business needs. Responsibilities Design and develop enterprise Generative AI applications using Python to meet business requirements Build and optimize Retrieval-Augmented Generation (RAG) pipelines to enhance knowledge retrieval accuracy Develop AI workflows and multi-agent systems leveraging LangGraph to orchestrate complex tasks Create and refine prompts and prompt templates for diverse Large Language Model (LLM) use cases Integrate enterprise knowledge repositories using Elastic Knowledge or Elasticsearch-based systems for efficient search Develop intelligent AI assistants, chatbots, and agentic AI solutions to improve user engagement Connect LLMs with enterprise APIs, databases, and document repositories to enable seamless data access Optimize retrieval quality, context management, and response accuracy to enhance AI performance Implement vector search and semantic search capabilities using vector databases such as Pinecone, Chroma, FAISS, Weaviate, or Milvus Evaluate, fine-tune, and monitor LLM performance to ensure reliability and effectiveness Collaborate with business stakeholders to translate AI use cases into technical solutions that drive value Follow AI governance, security, and responsible AI best practices to maintain compliance and ethical standards Required competencies and certifications Strong Python programming experience for AI application development Hands-on experience with LangGraph for building AI workflows and multi-agent systems Strong knowledge of Retrieval-Augmented Generation (RAG) techniques for knowledge retrieval Experience with Prompt Engineering and prompt optimization for LLMs Experience developing applications using Generative AI technologies Knowledge of Elastic Knowledge or Elasticsearch for enterprise search and knowledge retrieval Experience with LangChain ecosystem for AI development Experience integrating OpenAI, Azure OpenAI, Anthropic Claude, Gemini, or similar LLMs Knowledge of vector databases such as Pinecone, Chroma, FAISS, Weaviate, or Milvus for semantic search Experience building AI agents and multi-step workflows to automate complex processes Strong understanding of REST APIs and microservices for system integration Familiarity with Git, Docker, and CI/CD pipelines for version control and deployment automation