AI Platform Administrator

The AI Platform Administrator is responsible for the end-to-end administration, deployment, and governance of the organization's Large Language Model landscape, spanning both offline or self-hosted (on-premise or public/private cloud) models and paid or commercial LLM services such as Microsoft 365 Copilot, Azure OpenAI, Claude, Gemini, and other enterprise AI platforms.

This person is the primary point of contact for AI platform operations, user enablement, licensing, consumption monitoring, policy enforcement, risk management, and AI service optimization.

The role works closely with IT, Security, Legal, Compliance, Data Governance, and business stakeholders to maximize business value from AI investments while minimizing operational and regulatory risks.

The role is platform-agnostic in scope and applicable across AMETEK’s broader AI ecosystem, including Generative AI, Machine Learning platforms, AI Assistants, AI Agents, Knowledge Systems, and AI-powered business applications, with current focus on Microsoft 365 Copilot and related commercial LLM services.

Roles and Responsibilities:

• Deploy, configure, and maintain offline/self-hosted or on-premises LLMs on local servers, private or public cloud, or air-gapped environments.
• Manage model installation, version upgrades, patching, and lifecycle management for all self-hosted AI models.
• Optimize infrastructure (GPU/CPU, memory, storage) for performance, scalability, and cost-efficiency of locally hosted models.
• Configure and maintain model access controls, authentication, and integration with internal applications and APIs.
• Perform regular health checks, backups, and disaster recovery planning for offline AI environments.
• Manage subscriptions, accounts, and API access for paid/commercial LLMs (e.g. Microsoft 365 Copilot, Azure OpenAI, and similar enterprise platforms).
• Provision and de-provision user access, API keys, and workspace permissions across all paid LLM platforms.
• Coordinate with vendors on contract renewals, tiered plans, feature rollouts, and support escalations.
• Ensure integration of paid LLM services with enterprise applications, chatbots, and internal tools via APIs and connectors.