AI Platform Administrator

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Oversees AI platforms and environments, managing access provisioning, governance controls, and policy enforcement (such as DLP, security, and compliance).

• Creates reusable components (including prompts, connectors, APIs, and templates) to enhance the speed of AI solution delivery and encourage standardization across various use cases.

• Designs and sustains the foundational AI infrastructure, frameworks, and observability capabilities (telemetry, monitoring, metrics) essential for scalable, reliable, and governed AI operations.

• Implements security protocols, data handling regulations, and role-based access controls in partnership with InfoSec and Legal teams.

• Manages workspace configurations, user provisioning, single sign-on (SSO), and licensing processes.

• Integrates AI tools with core enterprise systems (such as HRIS, CRMs, and document repositories).

• Develops internal training resources, troubleshooting documentation, and monitors AI usage metrics to enhance value realization.

• Monitors platform performance, API error rates, and token usage to optimize operational expenses.

⛳️ Requirements

• 2–5+ years of experience in SaaS platform administration, IT operations, cloud computing, or systems administration.

• 5+ years of experience with APIs, cloud platforms (AWS, Azure, Google Cloud), and workflow automation tools.

• Strong ability to train staff, simplify technical concepts for business users, and handle support inquiries.

• A thorough understanding of data privacy laws, data residency requirements, and AI ethics.

🏝️ Benefits

• Compliance with Client’s responsible AI principles and Acceptable Use policy.

• Adherence to data residency, privacy (GDPR, HIPAA where applicable), and 21 CFR Part 11 controls where applicable.

• Third-party risk assessment and SOC 2 Type II (or equivalent) certification.

• Transparency regarding subcontractors and offshore delivery locations.

• Clarity on model providers, training data practices, and any utilization of client data for model enhancement (opt-out required).