Azure Generative AI Engineer

You are an experienced professional with 5 to 12 years of experience, looking for a Full-Time opportunity as an Azure Generative AI Engineer. Your primary skills include Data Science, Machine Learning, Python, AI, and Azure. You will be responsible for designing, developing, and deploying Generative AI applications using Python, FastAPI, Azure Durable Functions, and Azure OpenAI Services. You must build and implement Retrieval-Augmented Generation (RAG) pipelines for enterprise AI applications and work on end-to-end Generative AI projects. Your role involves integrating AI/ML search and data services such as Azure Cognitive Search, Cosmos DB, and other Azure-native tools. Automation of key components of the RAG workflow for ensuring production-grade performance and scalability is crucial. You will be evaluating, validating, and fine-tuning the outputs of Generative AI models for accuracy and relevance, implementing monitoring, observability, and guardrails to ensure responsible and secure use of AI technologies, and collaborating with cross-functional teams to deliver innovative AI solutions. To qualify for this role, you must have strong programming experience in Python, including frameworks like FastAPI and Flask. A deep understanding of Generative AI, LLMs, and RAG methodologies is essential. Proficiency in Azure cloud services, especially Azure OpenAI, Functions, AI Search, and Cosmos DB is required. Hands-on experience with machine learning, deep learning, and natural language processing (NLP) is a must. Familiarity with ML/DL frameworks such as TensorFlow, PyTorch, and libraries like scikit-learn, spaCy, etc., is expected. You should possess solid knowledge of machine learning algorithms, including GPTs, CNNs, RNNs, k-NN, Naive Bayes, SVM, and Decision Forests, along with experience in evaluating and fine-tuning LLM performance and implementing responsible AI practices. Preferred qualifications include certifications in Azure AI Engineer Associate or related fields. Experience working with managed LLMs beyond Azure OpenAI (e.g., OpenAI API, Anthropic, Cohere, etc.) and knowledge of DevOps, CI/CD, and infrastructure automation for AI pipelines are considered advantageous.,