Senior AI Platform Architect (MLOps & Responsible AI)

Brillio; Florida; On-site; USD 150,000 - 210,000; Full time

Job summary

Brillio is seeking a Senior AI Engineer to lead the design and deployment of enterprise-scale AI platforms in a Florida-based role. You will drive MLOps, governance and architecture for scalable AI adoption across business, data, and technology teams.

The ideal candidate brings 7+ years of data science/AI leadership, hands-on experience with GenAI and LLMs, and strong Python/MLOps skills to deliver production-ready solutions in cloud environments.

Qualifications

• 7+ years experience in data science and AI with leadership in enterprise-grade platforms.
• Experience designing and operationalizing enterprise AI platforms.

Responsibilities

• Lead design and architecture of end-to-end enterprise AI platforms with scalability and reliability.
• Define frameworks for model lifecycle management, MLOps/LLMOps, AI observability.
• Establish Responsible AI governance and guardrails for compliance and ethics.
• Drive platform-level decision-making to enable scalable enterprise AI adoption.
• Provide architectural leadership across business, data, technology and platform teams.
• Evaluate emerging AI technologies and assess applicability to enterprise platforms.
• Guide teams in selecting models, platforms and architectural patterns.
• Collaborate with senior stakeholders to define the enterprise AI roadmap.

Skills

Enterprise AI Platform

MLOps/LLMOps

Responsible AI

Cloud AI Platforms

GenAI / LLMs

Python ML Libraries

Education

Bachelor's degree in CS or related

Azure Data Scientist or IBM Data Science cert

Cloud architecture / AI platform certs

Tools

TensorFlow

PyTorch

scikit-learn

Job description

Brillio is seeking a Senior AI Engineer to lead the design and deployment of enterprise-scale AI platforms in a Florida-based role. You will drive MLOps, governance and architecture for scalable AI adoption across business, data, and technology teams.

The ideal candidate brings 7+ years of data science/AI leadership, hands-on experience with GenAI and LLMs, and strong Python/MLOps skills to deliver production-ready solutions in cloud environments.