AI Platform Engineering Lead – Google Cloud & Vertex AI

Huntington National Bank; Birmingham (MI); On-site; USD 93,000 - 189,000; Full time

Job summary

Huntington National Bank is seeking a Senior Manager to lead the AI Engineering Platforms on Google Cloud. You will define strategy, drive adoption of Vertex AI, and deliver enterprise-ready services with strong governance across teams.

The role focuses on building reusable capabilities, enabling secure and scalable AI deployments while working with Architecture, Data, Security, Risk, and Product leaders.

Qualifications

• Bachelor's Degree required.
• 10+ years in technology roles with 5+ years leading engineering/technology delivery teams.
• 3+ years building or modernizing cloud platforms.
• Experience leading large scale tech initiatives in regulated environments.
• Strong skills in stakeholder mgmt, communication, and influencing leaders.
• Experience with cloud-based platforms, DevOps, APIs, and cloud-native architectures.

Responsibilities

• Define and execute the vision, strategy, and roadmap for Huntington's AI Engineering Platform on Google Cloud.
• Lead adoption of Vertex AI and Gemini Enterprise Agent Platform capabilities.
• Establish reusable platform services, standards, and reference architectures.
• Evaluate new Google AI capabilities for the enterprise roadmap.
• Lead platform capabilities like agent development, model services, and knowledge retrieval.
• Drive observability, governance, security, and reliability across platforms.

Skills

Leadership

Stakeholder management

Communication

Cloud-native architectures

DevOps

CI/CD

Platform engineering

Education

Bachelor's Degree

Tools

Vertex AI

Gemini Enterprise Agent Platform

Agent Studio

ADK

BigQuery

Job description

Huntington National Bank is seeking a Senior Manager to lead the AI Engineering Platforms on Google Cloud. You will define strategy, drive adoption of Vertex AI, and deliver enterprise-ready services with strong governance across teams.

The role focuses on building reusable capabilities, enabling secure and scalable AI deployments while working with Architecture, Data, Security, Risk, and Product leaders.