Ai/ML Engineer & Gen AI Engineer

As a skilled GenAI and AI/ML Engineer with hands-on experience in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Python, and Generative AI application development, your role will involve designing, developing, and deploying AI-powered solutions using modern GenAI frameworks. You will collaborate 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. As a skilled GenAI and AI/ML Engineer with hands-on experience in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Python, and Generative AI application development, your role will involve designing, developing, and deploying AI-powered solutions using modern GenAI frameworks. You will collaborate 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 applic