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Senior, highly specialized Agentic AI architect reduces applicant density and competition.
Deep AI architecture, LLMOps, and knowledge-graph expertise make cross-industry transfers difficult.
Explicit 13+ years and numerous specialized Agentic AI, LLMOps, cloud, and architecture requirements.
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Design and architect enterprise-scale Agentic AI and Generative AI solutions with multi-agent collaboration and autonomous workflows.
Lead AI governance frameworks, observability standards, and best practices for AI deployment and lifecycle management.
Drive enterprise AI platform architecture, support AI engineering standards, and advise stakeholders on AI strategy and transformation initiatives.
13+ years of experience in AI/ML, Data Science, Intelligent Automation, or Generative AI with enterprise-scale solution architecture.
Proven expertise in multi-agent systems, advanced reasoning frameworks (ReAct, Plan-and-Execute, Reflection, Tree-of-Thoughts), and LLM-powered AI applications.
Proficiency in Python plus one or more of Java, JavaScript/TypeScript, C#, Go, along with experience in cloud platforms (AWS, Azure, or GCP) and containerization (Kubernetes).
Bachelor’s or master’s degree in Computer Science, Information Technology, or related field.
Experienced in designing and implementing scalable AI architectures involving multi-agent systems and advanced reasoning techniques.
Skilled in enterprise AI platforms including RAG, Knowledge Graphs, Semantic Search, vector and graph databases, with a strong engineering orientation.
Able to lead cross-functional teams, mentor technical staff, and engage with business and technology stakeholders for enterprise-wide AI initiatives.