Large Language Model Architect

• Project Role : Large Language Model Architect
• Project Role Description : Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data.
• Must have skills : Machine Learning (ML)
• Good to have skills : NA
• Minimum 12 year(s) of experience is required
• Educational Qualification : 15 years full time education

• Summary:
• Own the end-to-end architecture of complex enterprise agentic AI solutions. Ensure systems are scalable, secure, observable, reliable, and integrated with enterprise data and applications.
• Proven expertise selecting and governing LangGraph, OpenAI Agents SDK, Google ADK, Microsoft Foundry Agent Service, Vertex AI Agent Builder and Amazon Bedrock Agents, including MCP-based tool integration, identity, observability, evaluation and secure production deployment
• Must have architected and delivered production AI or ML systems at enterprise scale. Reference architectures, demos, or vendor-platform configuration alone are insufficient.

• Roles & Responsibilities:
• - Design multi-agent and tool-using AI architectures for complex business workflows.
• - Define orchestration, planning, state, memory, context, tool access, and human-approval patterns.
• - Make architecture decisions across models, retrieval, applications, data, APIs, security, and cloud.
• - Establish requirements for latency, throughput, resilience, cost, and auditability.
• - Guide engineering teams from design through deployment and operations.
• - Define evaluation, observability, guardrails, fallback, and incident-management patterns.
• - Lead architecture reviews and senior client discussions.

• Professional & Technical Skills:
• - LLM orchestration, tool calling, workflow engines, RAG, and memory architectures.
• - Distributed systems, APIs, event-driven architecture, cloud, and enterprise integration.
• - LLMOps, tracing, evaluation, security, identity, access control, and cost optimization.
• - Build-versus-buy and model-selection trade-offs.

15 years full time education

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