AI-Driven IT Systems Administrator — Remote

UserTesting; United States; On-site; USD 90,000 - 130,000; Full time

Job summary

UserTesting in the United States is seeking a proactive IT System Administrator to blend traditional IT administration with AI tooling. You will deploy and maintain MCP-based infrastructure, connect AI systems to internal data sources, and support ongoing integrations across the tech stack.

The role emphasizes hands-on work, scripting in Python or Bash, containerization with Docker, API-based integrations, and collaboration with Security, People Ops, and Engineering to advance AI enablement

Qualifications

• 5+ years of enterprise IT systems experience in a system administrator role.
• Hands-on MCP server setup and AI agent deployment experience.
• Scripting in Python or Bash and JSON/YAML for config and integration work.
• Familiarity with containerization (Docker) and API-based integrations.

Responsibilities

• Set up, configure, and maintain MCP servers that connect AI systems to internal tools and data sources.
• Enable and manage AI features within existing SaaS platforms and coordinate with vendors and stakeholders.
• Provision and support AI agent infrastructure: keys, permissions, auditing, and rate monitoring.
• Document architectures, runbooks, and troubleshooting guides; stay current on AI tooling.
• Collaborate with Security, People Ops, Engineering, and IT teams to improve onboarding and AI adoption.

Skills

IT System Admin

Python scripting

Bash scripting

Git version control

JSON/YAML parsing

Docker containers

API integrations

OAuth / SSO

Kanban method

Mentor IT staff

AI tooling knowledge

Tools

MCP servers

SaaS tooling

Okta integration

Job description

UserTesting in the United States is seeking a proactive IT System Administrator to blend traditional IT administration with AI tooling. You will deploy and maintain MCP-based infrastructure, connect AI systems to internal data sources, and support ongoing integrations across the tech stack.

The role emphasizes hands-on work, scripting in Python or Bash, containerization with Docker, API-based integrations, and collaboration with Security, People Ops, and Engineering to advance AI enablement