AI Engineer (GenAI / RAG / LangGraph / Python)

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