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Tier-1 brand and metro location increase applicants, but niche LLM/agent specialization reduces overall density.
Highly domain-specific ML/AI platform expertise required, limiting transferable candidates across unrelated industries.
Extensive technical mandates and architect-level expectations create high shortlist filtering.
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Design and build multi-model AI architectures leveraging Large Language Models (LLMs) for enterprise-scale applications.
Develop and maintain complex AI workflows, knowledge fabric systems, and integrate enterprise data stores with AI platforms.
Establish governance frameworks ensuring platform reliability, compliance, cost optimization, and integrate advanced components like Vector databases and Retrieval-Augmented Generation (RAG).
Degree requirements: B.E / M.E, B.Tech / M.Tech in a relevant field.
Experience Requirement: Not explicitly mentioned in the JD.
Technical skills: Expertise in AI architecture, LLMs, multi-agent systems, AI infrastructure optimization, Vector databases, and RAG implementations.
No explicit mention of notice period or location constraints.
Experienced in designing scalable AI ecosystems and orchestrating multi-model workflows in enterprise or cloud environments.
Proficient in implementing governance, compliance, and quality assurance frameworks for AI platforms.
Able to translate complex business requirements into integrated AI system solutions with a focus on performance and cost optimization.