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Tier-1 employer, Bangalore metro and mid-level GenAI role increases applicant density despite niche specialization.
Specialized GenAI and RAG experience is transferable but favors AI-focused product or advisory firms.
Explicit 4–7 years requirement plus mandatory GenAI, LLM and RAG skills enforce strict shortlisting.
Design, develop, and deploy Generative AI (GenAI) solutions focusing on production readiness and scalability.
Build and scale Retrieval-Augmented Generation (RAG) systems integrated with graph-based memory and multi-agent frameworks to enhance Large Language Models (LLMs).
Collaborate cross-functionally to translate business requirements into scalable, maintainable AI systems using Python and ensure software engineering best practices including CI/CD.
2 to 5 years of experience in AI/ML or software engineering with minimum 2 years specifically in building and deploying GenAI systems.
Proficiency with Large Language Models such as GPT-4, Claude 2/Gemini and hands-on experience with RAG systems and multi-agent frameworks like LangGraph, LangChain, or AutoGen.
Proficient in Python, with familiarity in cloud-native deployments including APIs, containers, and microservices.
Bachelor’s or Master’s degree in Engineering (BE/BTech/MTech), MCA, or MBA.
Experienced AI engineer strong in production-grade GenAI and agentic AI with hands-on knowledge of multi-agent orchestration and graph-based memory architectures.
Operates with solid software engineering discipline, ensuring code scalability, reliability, and maintainability across large AI systems.
Comfortable working in cross-functional teams to deliver real-world, scalable AI solutions leveraging cutting-edge AI tools and frameworks.