Gen AI Lead

Job Summary

We are looking for an experienced Gen AI Lead with strong hands-on expertise in designing, developing, deploying, and managing Generative AI solutions in production environments, particularly on Microsoft Azure.

The ideal candidate should have proven experience taking Generative AI and Large Language Model (LLM) solutions from Proof of Concept (POC) to enterprise-scale production, with strong knowledge of Azure AI services, LLMs, Retrieval-Augmented Generation (RAG), AI agents, and MLOps/LLMOps.

Key Responsibilities

• Lead the design, development, deployment, and productionization of Generative AI solutions.
• Architect and implement LLM-based applications, RAG pipelines, AI agents, and conversational AI solutions.
• Deploy and operationalize Generative AI applications on Microsoft Azure.
• Work with Azure OpenAI Service, Azure AI Search, Azure AI Foundry, Azure Machine Learning, and other relevant Azure services.
• Take Generative AI solutions from POC to pilot to production, ensuring scalability, reliability, security, and performance.
• Develop production-grade solutions using Python and relevant Generative AI and Machine Learning frameworks such as LangChain, LangGraph, and LlamaIndex.
• Design and optimize RAG architectures, including document ingestion, chunking, embeddings, vector databases, retrieval, reranking, and evaluation.
• Work with multiple LLMs and embedding models, evaluating them based on performance, cost, latency, and business requirements.
• Implement LLMOps/MLOps practices, including CI/CD, model evaluation, monitoring, logging, versioning, and governance.
• Ensure enterprise-grade security, data privacy, access control, Responsible AI, and compliance for Generative AI applications.
• Lead technical discussions with stakeholders and mentor Generative AI and Machine Learning engineers.
• Troubleshoot production issues and continuously optimize model performance, latency, scalability, and cost.

Mandatory Skills

• Strong hands-on experience in Generative AI and Large Language Models (LLMs).
• Proven production deployment experience with Generative AI solutions.
• Strong experience deploying Generative AI applications on Microsoft Azure.
• Experience with Azure OpenAI Service and Azure AI services.
• Strong knowledge of RAG, embeddings, vector databases, prompt engineering, and LLM evaluation.
• Experience with AI agents and Agentic AI is highly preferred.
• Strong programming experience in Python.
• Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.
• Experience with Docker, Kubernetes, REST APIs, and microservices.
• Understanding of Azure DevOps, CI/CD, MLOps/LLMOps, and production monitoring.
• Experience building scalable and secure enterprise AI architectures.

Good to Have

• Experience with Azure AI Foundry.
• Experience with Azure AI Search and vector search.
• Experience with OpenAI, Llama, Mistral, Gemini, Claude, or other LLMs.
• Experience with fine-tuning, LoRA/PEFT, or model customization.
• Knowledge of Generative AI observability and evaluation frameworks.
• Experience handling enterprise-scale Generative AI implementations.
• Strong architecture and technical leadership skills.

Key Requirement

Naukri Search Keywords

Use the following focused search strings to identify candidates with hands-on production experience in Generative AI and Azure.

Must-Have Search Filters

• Experience: 8–15 Years
• Keywords: GenAI, Azure, Azure OpenAI, LLM, RAG, Production, Deployment
• Prioritize profiles mentioning production implementation, production deployment, enterprise AI delivery, and Azure production experience.
• Candidates whose Generative AI experience consists only of basic POCs, personal experiments, or prototype chatbots should not be prioritized.