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Tier-1 brand, mid-level generalist AI role in Bangalore with broad GenAI requirements increases candidate competition.
Specialized GenAI and LLM tooling moderately favors AI-focused backgrounds over unrelated industries.
Explicit 4–7 years plus mandatory GenAI, LLM, RAG and production deployment skills tighten shortlisting.
Design, develop, and deploy production-ready Generative AI solutions leveraging Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs).
Build and scale multi-agent orchestration and reasoning systems using frameworks like LangChain, AutoGen, and LangGraph.
Collaborate cross-functionally to translate business needs into scalable, reliable, and maintainable AI-powered systems using strong software engineering practices.
2 to 5 years total experience in AI/ML or software engineering, including a minimum of 2 years hands-on experience with Generative AI.
Proficiency in Python and experience with LLM frameworks and libraries (e.g., LangChain, AutoGen, LangGraph).
Strong hands-on knowledge of RAG systems, multi-agent frameworks, and graph-based memory integration.
Education: Bachelor of Engineering (BE/BTech), Master of Engineering (MTech), Master of Business Administration (MBA), or MCA.
Experienced in deploying and scaling production-grade Generative AI and agentic AI solutions in enterprise environments.
Skilled in integrating and orchestrating multi-agent AI systems with graph-based memory and tool-using capabilities.
Familiar with cloud-native AI system deployments and strong software engineering discipline including CI/CD and version control.