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Design reusable patterns for RAG, semantic search, structured data access, and enterprise context
Design reusable patterns for agent orchestration, tool use, multi-step workflows, state management
Build the engineering harness around agents, including testing, evaluation, guardrails, retries
Build technical guardrails that enforce who can build what, what data and systems an agent can
Design defenses specific to agentic AI, including agent identity and access control
Extend and mature Coursera’s self-serve deployment path so AI-assisted, conversational development

12+ years of experience with clear progression from engineer to senior/staff engineer to architect
Hands-on experience with agentic AI frameworks and orchestration (e.g., LangGraph or comparable)
Familiarity with Model Context Protocol (MCP) or similar standards
Experience designing agent harnesses, evaluation frameworks, guardrails, testing, observability
Practical experience with enterprise context architecture, RAG, semantic search, or structured data
Practical experience with LLM cost and performance engineering—prompt caching, model routing, token

Enterprise Agentic AI Architect

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