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# AI / AI Platform Architect

- **Company:** HCL GLOBAL
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Applications Architecture, Cloud Engineering, Continuous Integration, Python (Programming Language), Machine Learning, Azure Machine Learning, Software Deployment, Retrieval-Augmented Generation, Large Language Models, IT Architecture, Model Validation, Generative AI, Agentic-AI, AI Platforms, Machine Learning Operations, AIOps, Databricks
- **Published:** October 29, 2026
- **Apply:** https://www.thejobnetwork.com/job/076e0505-a1c9-4fe6-91c5-5c3d6dda15dc/ai-ai-platform-architect

## About the Role

The candidate should have recent hands-on experience developing and deploying production-ready AI solutions and should be able to help teams accelerate the adoption of applied AI practices.

Essential Skills

 * Hands-on Python engineering and production AI/ML development.
 * Strong experience with Databricks and MLflow.
 * Experience with Azure AI Foundry is preferred.
 * Strong understanding of RAG and LLM application architecture.
 * Experience designing and implementing Agentic AI patterns and tool-based workflows.
 * Experience with LLM and model evaluation frameworks.
 * Ability to design and develop reusable AI accelerators, templates, and reference implementations.
 * Experience with AI Ops and production AI deployment practices.
 * Strong understanding of reusable AI skills, components, and frameworks.
 * Ability to work hands-on with engineering teams and contribute to production implementations., * Experience with Azure AI services and cloud-based AI platforms.
 * Experience building production-grade AI/ML applications.
 * Knowledge of AI governance, security, and responsible AI practices.
 * Experience with CI/CD and cloud deployment for AI applications.
 * Strong problem-solving and communication skills.

## Description

* Define AI architecture, technical direction, and implementation patterns.
 * Develop and deploy reusable AI acceleration frameworks and components.
 * Design and implement RAG and LLM-based applications.
 * Develop Agentic AI solutions and tool-based workflows.
 * Establish evaluation strategies and frameworks for LLMs and AI models.
 * Promote AI Ops practices for monitoring, evaluation, deployment, and production support.
 * Build reusable templates, skills, components, and reference architectures.
 * Collaborate closely with engineering teams to implement applied AI solutions.
 * Help teams improve development speed, scalability, and production readiness.
 * Drive the adoption of modern applied AI engineering practices.