Urgent opening For Ai/ML Engineer & Gen AI Engineer-Immediate Joiners (Chennai)

We are looking for a skilled GenA And Ai/MLI Engineer with hands-on experience in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Python, and Generative AI application development. The ideal candidate should have experience designing, developing, and deploying AI-powered solutions using modern GenAI frameworks while collaborating with cross-functional teams to build scalable and production-ready AI applications. Key Responsibilities Design, develop, and deploy Generative AI applications using Large Language Models (LLMs). Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise AI use cases. Develop scalable backend services using Python. Integrate LLMs with enterprise applications through APIs and microservices. Implement prompt engineering techniques to improve model accuracy and response quality. Build document ingestion, embedding, indexing, and semantic search solutions. Develop AI assistants, chatbots, and knowledge retrieval systems. Optimize LLM performance, latency, token usage, and inference costs. Work with vector databases for semantic search and contextual retrieval. Integrate AI applications with cloud services and external APIs. Collaborate with product, engineering, and business teams to deliver AI-driven solutions. Troubleshoot, debug, and continuously improve GenAI applications. Ensure AI solutions follow security, scalability, and best development practices. Requirements 4+ years of software development experience with strong expertise in Python. Minimum 1+ year of hands-on experience in Generative AI / LLM-based application development. Strong experience working with Retrieval-Augmented Generation (RAG) architecture. Hands-on experience with Large Language Models (OpenAI GPT, Azure OpenAI, Claude, Llama, Gemini, Mistral, or similar). Strong knowledge of Prompt Engineering and prompt optimization techniques. Experience with LangChain, LlamaIndex, CrewAI, or similar GenAI frameworks. Experience implementing embeddings, vector search, and semantic retrieval. Hands-on experience with vector databases such as Pinecone, ChromaDB, FAISS, Weaviate, Milvus, or Qdrant. Strong understanding of REST APIs, API integrations, and microservices. Experience integrating AI models with enterprise applications. Solid knowledge of JSON, API authentication, and data processing. Experience with Git, version control, and Agile development methodologies. Good understanding of Docker and containerized application deployment. Exposure to AWS, Azure, or Google Cloud AI services. Strong debugging, analytical, and problem-solving skills. Excellent verbal and written communication skills. Interested Candidate share directly resume on We are looking for a skilled GenA And Ai/MLI Engineer with hands-on experience in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Python, and Generative AI application development. The ideal candidate should have experience designing, developing, and deploying AI-powered solutions using modern GenAI frameworks while collaborating with cross-functional teams to build scalable and production-ready AI applications. Key Responsibilities Design, develop, and deploy Generative AI applications using Large Language Models (LLMs). Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise AI use cases. Develop scalable backend services using Python. Integrate LLMs with enterprise applications through APIs and microservices. Implement prompt engineering techniques to improve model accuracy and response quality. Build document ingestion, embedding, indexing, and semantic search solutions. Develop AI assistants, chatbots, and knowledge retrieval systems. Optimize LLM performance, latency, token usage, and inference costs. Work with vector databases for semantic search and contextual retrieval. Integrate AI applications with cloud services and external APIs. Collaborate with product, engineering, and business teams to deliver AI-driven solutions. Troubleshoot, debug, and continuously improve GenAI applications. Ensure AI solutions follow security, scalability, and best development practices. Requirements 4+ years of software development experience with strong expertise in Python. Minimum 1+ year of hands-on experience in Generative AI / LLM-based application development. Strong experience working with Retrieval-Augmented Generation (RAG) architecture. Hands-on experience with Large Language Models (OpenAI GPT, Azure OpenAI, Claude, Llama, Gemini, Mistral, or similar). Strong knowledge of Prompt Engineering and prompt optimization techniques. Experience with LangChain, LlamaIndex, CrewAI, or similar GenAI frameworks. Experience implementing embeddings, vector search, and semantic retrieval. Hands-on experience with vector databases such as Pinecone, ChromaDB, FAISS, Weaviate, Milvus, or Qdrant. Strong understanding of REST APIs, API integrations, and micros