Technology Manager - AI Platforms

aep; Columbus (OH); On-site; USD 140,000 - 210,000; Full time

Job summary

AEP is seeking a Manager of AI Platforms to lead the teams building and operating the enterprise AI foundation. You will shape the strategy, roadmap, and standard practices to deliver secure, scalable AI services for the entire organization.

The role requires strong leadership in platform engineering, ModelOps/LLMOps, and governance, with experience across cloud and on‑prem environments, and a focus on cost efficiency and reliability.

Qualifications

• Bachelor's degree in computer science, engineering, business, or related technical field.
• 8+ years of technology experience with 4–6 years of direct supervision preferred.
• Experience leading enterprise AI, ML, cloud, or platform engineering teams.
• Strong understanding of modern AI platform architecture and production AI operations.
• Knowledge of AI gateway technologies and patterns.

Responsibilities

• Define and execute the enterprise AI platform strategy and roadmap.
• Build and lead a high‑performing AI platform engineering and operations team.
• Establish platform standards, architecture patterns, and operational best practices.
• Evaluate emerging AI platform capabilities and determine fit within the enterprise tech ecosystem.
• Lead lifecycle management for platform services, observability, and governance.

Skills

AI Platform Leadership

Platform Engineering

Cloud & On‑Prem Architecture

ModelOps/LLMOps/AgentOps

Vendor & Cost Management

Observability & Monitoring

Security & IAM

Education

Bachelor's degree in computer science, engineering, business, or related technical field

Tools

AWS Bedrock

Azure AI Foundry

Microsoft Copilot

TrueFoundry

Portkey

LiteLLM

Job description

Job Summary

Help Us Power the Future by Building the Enterprise Foundation for AI at AEP!

At AEP, we're building the platforms and technical foundation needed to enable AI responsibly and at scale. We're looking for a Manager of AI Platforms to lead the teams responsible for engineering, operating, and continually improving that foundation. This role combines technology strategy, platform engineering, operational leadership, and people leadership to ensure enterprise AI capabilities are secure, reliable, scalable, and easy for teams across the company to use.

As the Manager of AI Platforms, you will define and execute the enterprise AI platform strategy and roadmap and lead the teams responsible for delivering and operating foundational AI services. You will establish platform standards and operating practices, drive reliability and cost effectiveness, manage key technology and vendor relationships, and work across technology and governance organizations to ensure AI capabilities are secure and well governed. Your team will provide reusable services and patterns that allow business and technology teams to build and deploy AI solutions more quickly and consistently.

Please note: This position is 100% onsite in Columbus, OH

Job Description

What you'll do:

• AI Platform Strategy & Leadership
  • Define and execute the enterprise AI platform strategy and roadmap.
  • Build and lead a high-performing AI platform engineering and operations team.
  • Establish platform standards, architecture patterns, and operational best practices.
  • Evaluate emerging AI platform capabilities and determine how they fit within the enterprise technology ecosystem.
• Platform Engineering & Operations
  • Lead the engineering, operation, support, and continuous improvement of enterprise AI platforms and foundational services.
  • Deliver secure, scalable, governed platform capabilities across cloud and on‑premises environments.
  • Oversee foundational capabilities including model access, agent frameworks, orchestration, RAG services, AI gateways, and observability.
  • Establish service-level objectives, operational metrics, monitoring, and continuous‑improvement practices.
  • Drive reliability, performance scalability, and cost optimization across the platform portfolio.
• ModelOps, LLMOps & AgentOps
  • Establish lifecycle practices for models, large language models, and AI agents, including evaluation, deployment, monitoring, and ongoing management.
  • Standardize platform services and operational patterns that help teams move AI solutions from development into production consistently.
  • Ensure appropriate observability and operational controls are incorporated throughout the AI lifecycle.
• Enterprise Enablement & Governance
  • Provide reusable platform services that allow business and technology teams to build and deploy AI solutions rapidly while operating within enterprise standards.
  • Partner closely with Enterprise and AI Architecture, Security, Data, Infrastructure, and Governance teams to support secure and compliant AI adoption.
  • Translate enterprise requirements into practical platform controls, standards, and services.
• Technology & Vendor Management
  • Manage strategic platform and vendor relationships, technology roadmaps, licensing, and technical evaluations.
  • Assess new AI technologies and platform capabilities for enterprise fit and value.
  • Manage platform costs and capacity with a focus on maximizing business value.

What we’re looking for:

• Education: Bachelor's degree in computer science, engineering, business, or related technical field is required.
• An equivalent combination of education and related experience may be considered.

Experience:

• In addition to any experience required above, 8 or more years of technology experience; 4-6 years of direct supervision experience preferred.

Preferred & Essential Skills

• Experience leading enterprise AI, ML, cloud, or platform engineering teams.
• Strong understanding of modern AI platform architecture and production AI operations.
• Experience with AWS Bedrock and AgentCore, Azure AI Foundry, and Microsoft Copilot.
• Experience establishing ModelOps, LLMOps, and AgentOps practices.
• Knowledge of AI gateway technologies and patterns, including platforms such as TrueFoundry, Portkey, and LiteLLM.
• Experience with model access, agent frameworks, orchestration, RAG architectures, observability, and AI lifecycle management.
• Strong understanding of cloud architecture, platform reliability, security, identity and access management, monitoring, and operational support.
• Experience defining platform metrics, service-level objectives, capacity strategies, and cost optimization practices.
• Experience evaluating technology vendors, managing platform roadmaps, and influencing vendor direction.
• Demonstrated ability to work across Architecture, Security, Data, Infrastructure, Governance, and delivery organizations.
• Strong people le