Architect

Area(s) of responsibility GenAI App Tech Architect – Azure OpenAI & Azure Cognitive Search We are looking for an experienced GenAI Architect to design, build, and scale enterprise-grade Generative AI solutions. The ideal candidate will have deep expertise in Azure AI services, Retrieval-Augmented Generation (RAG) architectures, and AI governance, along with the ability to collaborate across backend and frontend teams to deliver production-ready applications. Responsibilities: • Architect and implement end-to-end GenAI solutions using Azure ecosystem (Azure OpenAI, Cognitive Search, etc.) • Develop and enforce AI guardrails for safety, compliance, and responsible AI usage • Build scalable, secure, and high-performance AI systems aligned with enterprise standards • Implement conversational AI application using NodeJS,Azure OpenAI and Python • Integrate various AI technologies like OpenAI models, LangChain, Azure Cognitive Services (Cogniitve Search, Indexes,Indexers and APIS etc) to enable sophisticated natural language capabilities • Implementation of private endpoints across the Azure services leveraged for the application • Implement schemas, APIs, frameworks and platforms to operationalize AI models and connect them to conversational interfaces • Implement app logic for conversation workflows, context handling, personalized recommendations, sentiment analysis etc. • Build and deploy the production application on Azure while meeting security, reliability, and compliance standards • Create tools and systems for annotating training data, monitoring model performance, and continuously improving the application • Mentor developers and provide training on conversational AI development best practices • Build and productionize vector databases for the application on Azure cloud Requirements: • 10-12 years of overall technology experience in core application development • 5+ years experience leading 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