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Tier-1 brand, Bangalore metro, mid-level GenAI role and popular title increase candidate competition.
GenAI, PySpark and cloud skills are broadly transferable, though vector DB and RAG specialization add moderate domain bias.
Explicit 2–6 years plus mandatory GenAI, Python, PySpark, Azure, vector DB and deployment skills enforce strict filters.
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Design and develop scalable Generative AI-driven applications for software process automation and intelligent data retrieval.
Build and optimize Retrieval-Augmented Generation (RAG) pipelines using Large and Vision Language Models to enhance chatbot functionality and context understanding.
Collaborate cross-functionally to deploy AI solutions on Azure cloud; integrate Python backend services with cloud-native tools; maintain application performance, security, and reliability in production.
2–6 years of professional experience in relevant fields.
Strong proficiency in Python including frameworks like FastAPI or LangChain; solid skills in Pyspark for big data transformations.
Hands-on expertise with Generative AI technologies including LLMs (e.g., GPT, LLama), VLMs, and RAG architecture.
Experience deploying and managing applications on Azure cloud services including Azure Functions, App Services, and Azure AI services.
Experienced in designing and optimizing scalable AI applications with emphasis on Generative AI and RAG pipelines.
Proficient in integrating backend Python services with cloud-native Azure tools, indicating ability to manage deployment and CI/CD workflows effectively.
Comfortable working in a cross-functional team environment focused on AI solution delivery at a high technical staff level (T8/T9).