AI Architect

Position Overview

Seeking an experienced AI Architect to lead the design and implementation of an enterprise AI Agent Architecture. This role will be responsible for establishing the foundational framework for AI agents, developing initial proof-of-concept and production use cases, and providing knowledge transfer to internal teams to ensure long-term sustainability and scalability.

The ideal candidate will have expertise in AI/ML architecture, Generative AI, Agentic AI frameworks, LLM integration, and enterprise system design. This individual will work closely with business and technology stakeholders to identify opportunities for AI-driven automation, continuous monitoring, auditing, and operational process improvements.

Location: Chicago, IL (Hybrid) Employment Type: Contract

USC only - W2 Role (No C2C/1099)

Key Responsibilities

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Design and develop a scalable enterprise AI Agent Architecture.

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Lead the implementation of the first one to two AI agent use cases from concept through deployment.

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Evaluate and recommend AI platforms, frameworks, tools, and architectural patterns.

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Develop AI agents that support continuous monitoring, auditing, compliance, and operational workflows.

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Integrate AI solutions with existing enterprise applications, databases, APIs, and cloud platforms.

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Establish governance, security, observability, and performance standards for AI-driven solutions.

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Create reusable frameworks and best practices for future AI agent development.

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Collaborate with business stakeholders to identify opportunities for agentic AI adoption across various processes.

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Provide technical leadership, mentorship, and knowledge transfer to internal engineering and architecture teams.

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Document architecture, implementation standards, and operational procedures.

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Support the organization's AI strategy and roadmap development.

Preferred Qualifications

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Experience building AI agents for auditing, compliance, monitoring, risk management, or operational automation.

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Experience with Retrieval-Augmented Generation (RAG), vector databases, and AI orchestration frameworks.

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Familiarity with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar technologies.

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Experience working within large enterprise environments.

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Airline, transportation, logistics, or highly regulated industry experience is a plus.

What Success Looks Like

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Establish a scalable AI Agent Architecture for the organization.

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Successfully deliver one or more production-ready AI agent use cases.

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Enable internal teams through documentation, training, and knowledge transfer.

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Create a foundation for future AI agent adoption across auditing, monitoring, and operational business processes.