Gen AI Lead

As an experienced technical lead, your role will involve implementing an enterprise-grade conversational AI interface using technologies such as NodeJS, Python, LangChain, Azure OpenAI, and Azure Cognitive Services. Your responsibilities will include: - Implementing conversational AI applications utilizing NodeJS, Azure OpenAI, and Python. - Integrating various AI technologies like OpenAI models, LangChain, and Azure Cognitive Services to enhance natural language capabilities. - Setting up private endpoints across Azure services for the application. - Developing schemas, APIs, frameworks, and platforms to operationalize AI models and connect them to conversational interfaces. - Creating application logic for conversation workflows, context handling, personalized recommendations, and sentiment analysis. - Deploying the production application on Azure while adhering to security, reliability, and compliance standards. - Establishing tools and systems for annotating training data, monitoring model performance, and improving the application continuously. - Mentoring developers and providing training on conversational AI development best practices. - Building and operationalizing 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 knowledge of generative AI tools on Azure cloud. - Proficiency in Python and NodeJS with a focus on development. - Expertise in SharePoint indexes and Azure Form Recognizer tools. - Familiarity with LangChain, Azure OpenAI, and Azure Cognitive Search. - Experience in Retrieval Augmented Generation (RAG) and RLHF using Python. - Knowledge of vector databases on Azure cloud using PostgreSQL. - Exposure to tools like Pinecone, FAISS, Weaviate, or ChromaDB. - Experience in Prompt Engineering using LangChain or Llama Index. - Understanding of NLP techniques such as transformer networks, embeddings, and intent recognition. - Skills in Embedding and fine-tuning Azure OpenAI using MLOPS/LLMOPS pipelines. - Strong communication, DevOps, and collaboration skills would be a plus. As an experienced technical lead, your role will involve implementing an enterprise-grade conversational AI interface using technologies such as NodeJS, Python, LangChain, Azure OpenAI, and Azure Cognitive Services. Your responsibilities will include: - Implementing conversational AI applications utilizing NodeJS, Azure OpenAI, and Python. - Integrating various AI technologies like OpenAI models, LangChain, and Azure Cognitive Services to enhance natural language capabilities. - Setting up private endpoints across Azure services for the application. - Developing schemas, APIs, frameworks, and platforms to operationalize AI models and connect them to conversational interfaces. - Creating application logic for conversation workflows, context handling, personalized recommendations, and sentiment analysis. - Deploying the production application on Azure while adhering to security, reliability, and compliance standards. - Establishing tools and systems for annotating training data, monitoring model performance, and improving the application continuously. - Mentoring developers and providing training on conversational AI development best practices. - Building and operationalizing 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 knowledge of generative AI tools on Azure cloud. - Proficiency in Python and NodeJS with a focus on development. - Expertise in SharePoint indexes and Azure Form Recognizer tools. - Familiarity with LangChain, Azure OpenAI, and Azure Cognitive Search. - Experience in Retrieval Augmented Generation (RAG) and RLHF using Python. - Knowledge of vector databases on Azure cloud using PostgreSQL. - Exposure to tools like Pinecone, FAISS, Weaviate, or ChromaDB. - Experience in Prompt Engineering using LangChain or Llama Index. - Understanding of NLP techniques such as transformer networks, embeddings, and intent recognition. - Skills in Embedding and fine-tuning Azure OpenAI using MLOPS/LLMOPS pipelines. - Strong communication, DevOps, and collaboration skills would be a plus.