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Tier-1 brand, metro location, and broad AI skill requirements increase competition.
Core LLM, RAG, and cloud skills are highly transferable across industries.
Explicit 8–11 years plus mandatory LLM, RAG, vector DB and Java/Python requirements make filters strict.
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Design, build, and scale enterprise-grade AI-powered digital experiences focusing on Generative AI, Agentic AI, and Retrieval-Augmented Generation (RAG).
Develop multi-agent AI systems to automate customer journeys and business workflows with frameworks like LangChain, LangGraph, or CrewAI.
Build scalable backend microservices and APIs using Java and/or Python, integrating AI capabilities with cloud-native architectures and monitoring AI model performance and governance.
8-11 years of software engineering experience.
2+ years of hands-on experience building applications with Large Language Models (LLMs) or Generative AI.
Strong programming skills in Java and/or Python, with experience building REST APIs and microservices.
Experience with GPT, Claude, Gemini or equivalent LLMs, Agent AI frameworks (LangChain, LangGraph, CrewAI), Retrieval-Augmented Generation (RAG), and vector databases.
Experienced in deploying production-grade AI solutions using modern LLMs and agent frameworks in cloud-native environments.
Skilled in combining AI technologies with backend microservices to create scalable, customer-facing applications.
Strategic focus on operationalizing AI through monitoring, governance, cost optimization, and driving organizational adoption of emerging AI technologies.