Senior Manager, AI Engineering Platforms

Jobtailor

Alabama

On-site

USD 180,000 - 240,000

Full time

4 days ago

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Job summary

Huntington's AI Engineering Platform team seeks a visionary leader to define and execute the strategy and roadmap for Google Cloud-based AI capabilities. You will drive Vertex AI and Gemini Enterprise adoption, establish standards, and orchestrate enterprise-grade services across security, governance, and observability.

Lead cross-functional teams to deliver scalable, secure, and compliant platform services with a focus on efficiency, cost optimization, and developer productivity in a highly

Qualifications

Bachelor's degree required.
Minimum 10 years of related technology experience.
Minimum 5 years leading engineering/ platform teams.
Minimum 3 years building, operating, or modernizing cloud-based platforms.
Experience leading large-scale technology initiatives in regulated environments.
Experience developing technology roadmaps and target-state architecture.
Experience managing cross-functional teams and vendors.
Experience with secure, highly available services.
Experience with software engineering, DevOps, CI/CD, APIs, cloud-native architectures.
Strong stakeholder management and leadership skills.
Preferred: GCP Vertex AI, BigQuery, Cloud Run, Pub/Sub, AlloyDB, and enterprise AI capabilities.
Preferred: Experience with generative AI and agent-based platforms.
Preferred: Regulatory and enterprise architecture collaboration.
Preferred: Financial services or highly regulated industry experience.

Responsibilities

Define and execute 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.
Evaluate emerging Google AI capabilities for enterprise roadmap.
Lead enterprise capabilities across agent development, orchestration, model and reasoning services, knowledge retrieval, memory/state management, runtime, governance, security, and observability.
Provide strategic and operational leadership for Google Cloud AI platform services.
Create paved road via reusable frameworks, accelerators, SDKs, and standards.
Improve developer productivity through platform automation and self-service capabilities.
Drive adoption, maturity, and cost-efficiency across AI/agent solution teams.
Establish enterprise-grade operational capabilities, observability standards, and support models.
Ensure platform reliability, security, compliance, and scalability.
Collaborate with Architecture, Engineering, Data, Infrastructure, Security, Risk, and Product leaders to operationalize enterprise AI capabilities.

Skills

Platform leadership

Cloud strategy

Vertex AI

CI/CD

DevOps

Stakeholder mgmt

Cross-functional teams

Education

Bachelor's Degree

Tools

ADK

Gemini Enterprise

Agent Runtime

BigQuery

Cloud Run

Pub/Sub

AlloyDB

Job description

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
Evaluate and incorporate emerging Google AI capabilities into the enterprise platform roadmap
Lead enterprise capabilities across agent development and orchestration, model and reasoning services, knowledge and retrieval, memory and state management, runtime, tools and execution, governance, security and observability
Provide strategic and operational leadership for Google Cloud AI platform 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
Partner with Architecture, Engineering, Data, Infrastructure, Security, Risk, and Product leaders to define platform strategy and operationalize enterprise AI capabilities

Requirements

Bachelor's Degree
Minimum 10 years of related technology experience
Minimum 5 years of experience leading engineering, platform, or technology delivery teams
Minimum 3 years of experience building, operating, or modernizing cloud-based platforms
Experience leading large-scale technology initiatives in a complex, highly regulated environment
Experience developing and executing technology roadmaps, platform strategies, and target-state architecture
Experience managing cross-functional teams, vendors, and strategic technology partners
Experience establishing and operating highly available, secure, and resilient technology services
Experience with software engineering, platform engineering, DevOps, CI/CD, APIs, and cloud-native architectures
Experience driving operational excellence through observability, monitoring, incident management, and service reliability practices
Strong stakeholder management, communication, and influencing skills with the ability to engage technical and non-technical leaders
Demonstrated experience building, coaching, and developing high-performing engineering teams
Preferred: Experience with Google Cloud Platform (GCP), including Vertex AI, BigQuery, Cloud Run, Pub/Sub, AlloyDB, and cloud-native platform services
Preferred: Experience with generative AI, agentic systems, AI/ML platforms, and enterprise AI solution delivery
Preferred: Experience with Vertex AI, Gemini Enterprise Agent Platform, Agent Development Kit (ADK), Agent Runtime, and AI governance capabilities
Preferred: Experience implementing enterprise AI capabilities such as agent development and orchestration, model and reasoning services, knowledge and retrieval, memory and state management, runtime and execution, governance and observability
Preferred: Experience developing enterprise platforms, paved roads, reusable services, frameworks, and engineering accelerators
Preferred: Experience working with enterprise architecture, information security, risk, compliance, and regulatory teams
Preferred: Financial services or other highly regulated industry experience

Core Competencies

Demonstrates expertise in leading the development and operationalization of AI Engineering Platforms on Google Cloud, with a focus on Vertex AI and Gemini Enterprise Agent capabilities. Proven ability to establish engineering standards, drive platform automation, and ensure compliance and security in a highly regulated environment.

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