AI Architect

hudsonmanpower; Chicago (IL); Hybrid; USD 120,000 - 160,000; Full time

Job summary

hudsonmanpower is looking for an experienced AI Architect in Chicago, IL, to lead the design and implementation of an AI Agent Architecture. This role focuses on creating a scalable framework for AI agents and deploying production use cases.

The ideal candidate will have strong expertise in AI/ML architecture, LLMs, and will work closely with diverse stakeholders to drive AI initiatives. The position is hybrid, offering flexibility for in-office and remote work.

Qualifications

• 8+ years of experience in Software Architecture or Enterprise Architecture.
• 3+ years of experience designing and implementing AI/ML solutions.
• Strong understanding of Agentic AI concepts and workflows.

Responsibilities

• Design and develop a scalable enterprise AI Agent Architecture.
• Implement AI agent use cases from concept through deployment.
• Collaborate with stakeholders to identify AI adoption opportunities.

Skills

AI Architecture

Generative AI

Agentic AI

Large Language Models (LLMs)

API Integration

Cloud Platforms (AWS, Azure, GCP)

AI Governance

Job description

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

• Design and develop a scalable enterprise AI Agent Architecture.
• Lead the implementation of the first one to two AI agent use cases from concept through deployment.
• Evaluate and recommend AI platforms, frameworks, tools, and architectural patterns.
• Develop AI agents that support continuous monitoring, auditing, compliance, and operational workflows.
• Integrate AI solutions with existing enterprise applications, databases, APIs, and cloud platforms.
• Establish governance, security, observability, and performance standards for AI‑driven solutions.
• Create reusable frameworks and best practices for future AI agent development.
• Collaborate with business stakeholders to identify opportunities for agentic AI adoption across various processes.
• Provide technical leadership, mentorship, and knowledge transfer to internal engineering and architecture teams.
• Document architecture, implementation standards, and operational procedures.
• Support the organization’s AI strategy and roadmap development.

Preferred Qualifications

• Experience building AI agents for auditing, compliance, monitoring, risk management, or operational automation.
• Experience with Retrieval‑Augmented Generation (RAG), vector databases, and AI orchestration frameworks.
• Familiarity with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar technologies.
• Experience working within large enterprise environments.
• Airline, transportation, logistics, or highly regulated industry experience is a plus.

What Success Looks Like

• Establish a scalable AI Agent Architecture for the organization.
• Successfully deliver one or more production‑ready AI agent use cases.
• Enable internal teams through documentation, training, and knowledge transfer.
• Create a foundation for future AI agent adoption across auditing, monitoring, and operational business processes.

Required Qualifications

• 8+ years of experience in Software Architecture, Solution Architecture, or Enterprise Architecture.
• 3+ years of experience designing and implementing AI/ML or Generative AI solutions.
• Strong understanding of Agentic AI concepts, autonomous workflows, and AI orchestration frameworks.
• Experience working with Large Language Models (LLMs) such as OpenAI, Anthropic, Google Gemini, or similar platforms.
• Experience designing AI solutions using cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Strong experience with API integrations, microservices architecture, and enterprise application design.
• Knowledge of AI governance, model monitoring, security, and responsible AI practices.
• Experience leading technical initiatives and collaborating with cross‑functional teams.Excellent communication, documentation, and stakeholder management skills.

Key Skills

• AI Architecture
• Generative AI
• Agentic AI
• Large Language Models (LLMs)
• AI Agents
• OpenAI / Gemini / Anthropic
• LangChain / LangGraph / CrewAI
• RAG Architecture
• Vector Databases
• Cloud Platforms (AWS, Azure, GCP)
• API Integration
• Enterprise Architecture
• Solution Design
• Knowledge Transfer
• AI Governance