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Tier-1 brand, mid-level AI role, metro location create high applicant competition.
Specialized GenAI and agentic AI experience required, limiting cross-industry transferability.
Explicit years, mandatory GenAI hands-on experience and LLM tooling make filtering highly strict.
Design, develop, and deploy Generative AI (GenAI) solutions focused on production readiness and enterprise use cases using Retrieval-Augmented Generation (RAG) and multi-agent frameworks.
Build and scale AI systems integrating LLMs like GPT-4, graph-based memory, tool-using agents, and multi-agent orchestration (e.g., AutoGen, LangGraph, LangChain).
Write scalable, maintainable code primarily in Python, collaborating cross-functionally to translate business needs into AI-powered scalable systems while ensuring software engineering best practices.
2 to 5 years total experience in AI/ML or software engineering with at least 2 years hands-on in building and deploying GenAI systems.
Proficiency in Python and experience with LLMs such as GPT-4, Claude 2, Gemini, and frameworks like LangChain, AutoGen, or LangGraph.
Educational qualification: BE/BTech, MCA, MTech, or MBA.
Experience with cloud-native deployments (APIs, containers, microservices) and solid software engineering practices including version control, testing, and CI/CD.
Candidate with deep expertise in Generative AI technologies, multi-agent AI systems, and advanced AI tooling for production-scale deployment.
Experience collaborating across business and technical teams to deliver scalable, enterprise-ready AI solutions leveraging RAG and agentic AI.
Background in software engineering with demonstrated ability to maintain reliability, scalability, and clean code within AI/ML production environments.