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Niche senior LLM/Azure skillset and lesser-known employer reduce applicant density despite Pune metro.
Specialized LLM and Azure tooling increases domain bias, though ML skills remain broadly transferable.
Mandatory 7+ years plus deep LLM, Azure, LangChain, graph and MLOps expertise makes screening strict.
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Own end-to-end design, development, deployment, and continuous improvement of production-grade Generative AI solutions using Azure AI Foundry.
Build and operationalize advanced Retrieval Augmented Generation (RAG) pipelines, knowledge graphs, multi-agent LLM reasoning workflows, and computer vision models.
Lead AI/ML lifecycle management including CI/CD, containerized deployments, and collaborate cross-functionally to translate business problems into scalable AI solutions.
7+ years of AI/ML Engineering experience, with at least 2+ years hands-on developing production LLM applications.
Expert-level Python and strong software engineering skills.
Strong hands-on experience with Microsoft Azure AI ecosystem including Azure AI Foundry, Azure AI Search, Azure ML, Azure OpenAI Service, and Azure Custom Vision.
Experience with LangChain and LangGraph for multi-agent LLM workflows and knowledge graphs relevant technologies such as Azure Cosmos DB Gremlin and Neo4j.
Deep expertise in Generative AI, Agentic LLM workflows, RAG pipelines, and combined application of vector search, graph analytics, and computer vision within Azure AI.
Proven ability to manage full AI/ML solution lifecycle including deployment, monitoring, MLOps, and CI/CD in a hybrid cloud environment.
Strategic collaborator able to engage cross-functional teams (Industrial Engineering, Product, IT) to drive AI adoption and integrate domain-specific retrieval and multi-agent reasoning into production systems.