AI Engineer (GenAI / RAG / LangGraph / Python)

Description

• 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)
• Experience with Prompt Engineering and prompt optimization.

Experience developing applications using

• Generative AI technologies.
• Knowledge of Elastic Knowledge / Elasticsearch for enterprise search and knowledge retrieval.
• Experience with LangChain ecosystem.
• Experience integrating OpenAI, Azure OpenAI, Anthropic Claude, Gemini, or similar LLMs.
• Knowledge of vector databases such as Pinecone, Chroma, FAISS, Weaviate, or Milvus.
• Experience building AI agents and multi-step workflows.
• Strong understanding of REST APIs and microservices.
• Familiarity with Git, Docker, and CI/CD pipelines.