Senior Manager, AI Engineering Platforms
Listed on 2026-09-20
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Management
AI Business & Operations
Senior Manager, AI Engineering Platforms Building the Google-powered foundation that enables enterprise AI at scale.
Lead the strategy, engineering, and operation of Huntington's AI Engineering Platform on Google Cloud, delivering the shared capabilities, services, guardrails, and developer experiences that enable teams across the enterprise to build, deploy, govern, and operate AI solutions safely and at scale.
Description Senior Manager, AI Engineering Platforms Building the Google-powered foundation that enables enterprise AI at scale.Lead the strategy, engineering, and operation of Huntington's AI Engineering Platform on Google Cloud, delivering the shared capabilities, services, guardrails, and developer experiences that enable teams across the enterprise to build, deploy, govern, and operate AI solutions safely and at scale.
Responsible for the enterprise AI engineering ecosystem including Vertex AI, Gemini Enterprise Agent Platform, agent development services, model management, knowledge and retrieval capabilities, memory and state services, runtime execution, observability, platform governance, and engineering enablement. This role drives the evolution of Huntington's AI Engineering paved road, transforming AI from isolated solutions into reusable enterprise capabilities that accelerate innovation while maintaining security, resiliency, and regulatory compliance.
Partner closely with Architecture, Engineering, Data, Infrastructure, Security, Risk, and Product leaders to define platform strategy, establish engineering standards, and operationalize enterprise AI capabilities across the organization.
Key Responsibilities AI Platform Strategy & Leadership- Define and execute the vision, strategy, and roadmap for Huntington's AI Engineering Platform on Google Cloud.
- Lead adoption and operationalization of Vertex AI and Gemini Enterprise Agent Platform capabilities.
- Establish reusable platform services, engineering standards, and reference architectures that accelerate AI delivery across the enterprise.
- Evaluate and incorporate emerging Google AI capabilities into the enterprise platform roadmap.
- Agent Development & Orchestration
- Model & Reasoning Services
- Knowledge & Retrieval
- Memory & State Management
- Runtime, Tools & Execution
- Governance, Security & Observability
- Vertex AI and Gemini Enterprise Agent Platform
- Agent Studio and Agent Development Kit (ADK)
- Model Garden and Gemini model services
- Agent Runtime and Code Execution
- Memory Bank, Sessions, and Context Services
- Vertex AI Search and Vector Search
- Big Query-powered AI and knowledge services
- AI observability, monitoring, security, and governance services
- Create the AI Engineering paved road through reusable frameworks, accelerators, SDKs, and engineering standards.
- Improve developer productivity through platform automation and self-service capabilities.
- Drive engineering adoption and maturity across AI and agent-based solution teams.
- Establish enterprise-grade operational capabilities, observability standards, and support models.
- Ensure platform reliability, scalability, security, and compliance.
- Drive cost optimization, operational excellence, and continuous platform improvement.
- Faster delivery of AI-powered business capabilities.
- Increased adoption of reusable platform services.
- Improved developer productivity and engineering efficiency.
- Secure, governed, and compliant AI operations.
- Reduced duplication across AI initiatives.
- Scalable enterprise AI capabilities built on Google Cloud.
- Bachelor'…
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