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