AI Engineer (GenAI / RAG / LangGraph / Python)

Responsibilities

• ● We are looking for a highly skilled AI Engineer with strong expertise in Generative AI, Prompt Engineering, Retrieval-Augmented Generation (RAG), LangGraph, Elastic Knowledge, and Python. The ideal candidate should have experience designing, developing, and deploying enterprise-grade AI applications powered by Large Language Models (LLMs) and modern AI frameworks.
• ● The candidate should be capable of building intelligent AI agents, orchestrating complex workflows using LangGraph, integrating enterprise knowledge bases, and developing scalable GenAI solutions for business use cases.
• ● Key Responsibilities
• ● Design and develop enterprise Generative AI applications using Python.
• ● Build and optimize Retrieval-Augmented Generation (RAG) pipelines for knowledge retrieval.
• ● Develop AI workflows and multi-agent systems using LangGraph.
• ● Create effective prompts and prompt templates for various LLM use cases.
• ● Integrate enterprise knowledge repositories using Elastic Knowledge or Elasticsearch-based knowledge systems.
• ● Develop intelligent AI assistants, chatbots, and agentic AI solutions.
• ● Connect LLMs with enterprise APIs, databases, and document repositories.
• ● Optimize retrieval quality, context management, and response accuracy.
• ● Implement vector search and semantic search capabilities.
• ● Evaluate, fine-tune, and monitor LLM performance.
• ● Collaborate with business stakeholders to understand AI use cases and translate them into technical solutions.
• ● Follow AI governance, security, and responsible AI best practices.
• ● Required Skills
• ● Strong Python programming experience.
• ● Hands-on experience with LangGraph.
• ● Strong knowledge of Retrieval-Augmented Generation (RAG).
• ● Knowledge of Elastic Knowledge / Elasticsearch for enterprise search and knowledge retrieval.