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:

Administration:

• 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.
• Stay current on new model releases, pricing changes, and feature updates from commercial LLM vendors.

Tracking and Governance:

• Establish and maintain a centralized inventory & dashboard of all LLM licenses, subscriptions, and API keys (offline and paid) across the organization.
• Continuously monitor usage metrics (tokens consumed, API calls, active seats/users, compute hours) for each LLM platform.
• Track license utilization against entitlements to identify underused, overused, or idle licenses, and recommend right-sizing.
• Define and enforce governance policies for AI/LLM usage, including acceptable use, data handling, and access approval workflows.
• Set up automated alerts and periodic reports for usage thresholds, budget overruns, and anomalous consumption patterns.
• Conduct periodic license audits and reconciliation against vendor invoices and contracts.
• Maintain documentation of usage policies, entitlements, renewal dates, and compliance requirements for each LLM.
• Partner with Finance to forecast, budget, and optimize spend on paid LLM subscriptions.
• Ensure compliance with organizational IT policies, data protection regulations, and applicable AI governance standards.

User Enablement and Training

• Develop and maintain user onboarding materials, quick-start guides, and training content for AI platform adoption.
• Deliver training sessions and internal communications to drive awareness and responsible use of AI tools.
• Serve as the first point of contact for end-user questions on licensing, access, and platform capabilities.

Reporting:

• Prepare and present regular reports and dashboards to IT leadership on LLM usage, license utilization, cost trends, and governance compliance.
• Recommend and drive process improvements, automation, and tooling to streamline LLM administration and governance.
• Evaluate emerging LLM platforms and tools and provide recommendations on adoption or migration.

Candidate Requirements:

Experience:

• 10+ years of overall IT administration and systems/application administration experience, including at least 4 years focused on AI/ML platform management.

Required Skills:

• Hands-on experience managing self-hosted or offline LLM deployment and paid/commercial LLM platforms (e.g. Microsoft 365 Copilot, Azure OpenAI, Anthropic Claude, Google Gemini).
• Strong experience with Microsoft Power Platform, including Power Automate and Power Apps for provisioning workflows.
• Experience with cloud platforms (Azure, AWS, etc.) and containerization (Docker/Kubernetes) for hosting offline models.
• Proficient scripting skills (Python/Bash/PowerShell) for automation of monitoring and reporting.
• Strong analytical and problem-solving skills.
• Strong communication and stakeholder management skills.
• Demonstrated ability and willingness to use AI tools to improve productivity, decision-making, work quality, and to reduce costs. The successful candidate must be able to identify appropriate AI use cases and critically evaluate AI-generated outputs. 

Qualifications:

• Bachelor’s degree in Engineering, Computer Science, Electronics, or a closely related field.
• Any AI related certification or degree is an added advantage.
• Microsoft Platform certification or related Microsoft certifications are a plus.