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Mid-level, popular AI role in a metro with broad LLM requirements increases applicant competition.
Specialized LLM and agent engineering skills are transferable across industries but require ML-focused backgrounds.
Explicit 5-7 years and mandatory LLM, multi-agent, and production experience make screening strict.
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Design and deploy scalable multi-agent AI systems utilizing Large Language Models (LLMs) for content generation, evaluation, and orchestration with human-in-the-loop controls.
Build production-grade LLM-powered generation pipelines including Retrieval-Augmented Generation (RAG) and AI evaluation frameworks for quality, accuracy, and compliance.
Optimize AI systems for cost, latency, scalability, and implement observability and responsible AI guardrails in collaboration with cross-functional teams.
5-7 years of relevant work experience in AI engineering or related roles.
Strong proficiency in Python with hands-on experience building production-grade AI applications involving LLMs and generative AI.
Hands-on experience with multi-agent AI frameworks such as LangGraph, LangChain, CrewAI, or AutoGen.
Location requirement: Chennai, Tamil Nadu, India (Explicitly mentioned).
Experienced in taking LLM-powered AI products from prototype to production with scalability and reliability focus.
Skilled in multi-agent architectures combining generation, evaluation (LLM-as-a-Judge), and orchestration for autonomous AI agents.
Knowledgeable about cloud ML deployment practices, AI observability, prompt engineering, and responsible AI principles.