About the Role: AI Engineer with a strong background in Azure-based AI solutions. Candidate should have hands-on experience working with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agent development. Proficiency in Python toolkits is highly preferred. This role offers an opportunity to work on cutting-edge AI projects, leveraging state-of-the-art tools to build intelligent and scalable solutions. Key Responsibilities: • Design, develop, and deploy AI solutions leveraging Azure AI services. • Implement LLM-powered applications, fine-tuning models for specific use cases. • Develop Retrieval-Augmented Generation (RAG) workflows to enhance AI-based search and decision-making. • Build and optimize AI agents for automation, recommendation, and conversational AI. • Utilize Python toolkits for AI model development, testing, and deployment. • Work with cross-functional teams to integrate AI solutions into existing platforms. • Ensure scalability, efficiency, and reliability of AI models and pipelines. • Stay up to date with advancements in AI, machine learning, and cloud computing. Required Skills & Experience: • 3+ years of experience in AI/ML engineering. • Hands-on expertise with Azure AI services (e.g., Azure OpenAI, Azure Machine Learning, Cognitive Services). • Proven experience in working with LLMs, including fine-tuning and prompt engineering. • Strong knowledge of RAG techniques and vector search implementation. • Experience in designing and deploying AI agents. • Proficiency in Python and its AI/ML-related libraries (e.g., TensorFlow, PyTorch, LangChain, Hugging Face, FastAPI). • Experience with Vector Databases (e.g., Pinecone, FAISS, Weaviate) and GraphQL (preferred). • Familiarity with MLOps practices, CI/CD for AI models, and cloud-based deployment. • Strong problem-solving skills and ability to work in a collaborative environment. Nice-to-Have: • Experience with Kubernetes, Docker, and cloud-native AI solutions. • Understanding of Natural Language Processing (NLP) and Knowledge Graphs. • Background in Reinforcement Learning with Human Feedback (RLHF). • Previous experience working with enterprise AI applications.