Gen AI Lead - Azure OpenAI & Cognitive Search

You are an experienced technical lead who will be responsible for implementing an enterprise-grade conversational AI interface leveraging technologies like NodeJS, Python, LangChain, Azure OpenAI, and Azure Cognitive Services. Your key responsibilities will include: - Implementing conversational AI application using NodeJS, Azure OpenAI, and Python - Integrating various AI technologies like OpenAI models, LangChain, Azure Cognitive Services (Cognitive Search, Indexes, Indexers, and APIs, etc.) to enable sophisticated natural language capabilities - Implementing private endpoints across the Azure services leveraged for the application - Implementing schemas, APIs, frameworks, and platforms to operationalize AI models and connect them to conversational interfaces - Implementing app logic for conversation workflows, context handling, personalized recommendations, sentiment analysis, etc. - Building and deploying the production application on Azure while meeting security, reliability, and compliance standards - Creating tools and systems for annotating training data, monitoring model performance, and continuously improving the application - Mentoring developers and providing training on conversational AI development best practices - Building and productionizing vector databases for the application on Azure cloud Qualifications required for this role include: - 7+ years of overall technology experience in core application development - 2+ years of experience leading the development of AI apps and conversational interfaces - Hands-on implementation-centric knowledge of generative AI tools on Azure cloud - Deep, hands-on, and development proficiency in Python and NodeJS - Hands-on expertise of SharePoint indexes and data/file structures (Azure SQL) - Hands-on knowledge of Azure Form Recognizer tools - Experience with LangChain, Azure OpenAI, and Azure Cognitive Search - Retrieval Augmented Generation (RAG) and RLHF (Reinforcement Learning from Human Feedback) using Python - Vector databases on Azure cloud using PostgreSQL - Pinecone, FAISS, Weaviate, or ChromaDB - Prompt Engineering using LangChain or Llama Index - Knowledge of NLP techniques like transformer networks, embeddings, intent recognition, etc. - Hands-on skills on Embedding and finetuning Azure OpenAI using MLOPS/LLMOPS pipelines - Good to have - Strong communication, DevOps, and collaboration skills You are an experienced technical lead who will be responsible for implementing an enterprise-grade conversational AI interface leveraging technologies like NodeJS, Python, LangChain, Azure OpenAI, and Azure Cognitive Services. Your key responsibilities will include: - Implementing conversational AI application using NodeJS, Azure OpenAI, and Python - Integrating various AI technologies like OpenAI models, LangChain, Azure Cognitive Services (Cognitive Search, Indexes, Indexers, and APIs, etc.) to enable sophisticated natural language capabilities - Implementing private endpoints across the Azure services leveraged for the application - Implementing schemas, APIs, frameworks, and platforms to operationalize AI models and connect them to conversational interfaces - Implementing app logic for conversation workflows, context handling, personalized recommendations, sentiment analysis, etc. - Building and deploying the production application on Azure while meeting security, reliability, and compliance standards - Creating tools and systems for annotating training data, monitoring model performance, and continuously improving the application - Mentoring developers and providing training on conversational AI development best practices - Building and productionizing vector databases for the application on Azure cloud Qualifications required for this role include: - 7+ years of overall technology experience in core application development - 2+ years of experience leading the development of AI apps and conversational interfaces - Hands-on implementation-centric knowledge of generative AI tools on Azure cloud - Deep, hands-on, and development proficiency in Python and NodeJS - Hands-on expertise of SharePoint indexes and data/file structures (Azure SQL) - Hands-on knowledge of Azure Form Recognizer tools - Experience with LangChain, Azure OpenAI, and Azure Cognitive Search - Retrieval Augmented Generation (RAG) and RLHF (Reinforcement Learning from Human Feedback) using Python - Vector databases on Azure cloud using PostgreSQL - Pinecone, FAISS, Weaviate, or ChromaDB - Prompt Engineering using LangChain or Llama Index - Knowledge of NLP techniques like transformer networks, embeddings, intent recognition, etc. - Hands-on skills on Embedding and finetuning Azure OpenAI using MLOPS/LLMOPS pipelines - Good to have - Strong communication, DevOps, and collaboration skills