IT Support Ops Expert, AI Data Trainer

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We connect people with hands-on roles that shape how modern AI systems behave—work that’s remote, flexible, and often accessible without prior AI experience.

Join a community that helps train the next generation of AI agents. OpenTrain supports contributors through project listings, clear instructions, and a path to grow your AI-training skills.

About AI Training Work

AI training (also called data labeling or human feedback work) is the human backbone of machine learning: people annotate, evaluate, and rate examples so models learn correct behavior. This job focuses on training conversational or decision-making AI agents to handle B2B IT support scenarios.

Typical benefits of this kind of work include fully remote tasks, flexible hours, and direct impact on how real-world AI systems respond in professional environments.

The Role

We’re hiring experienced IT Support and IT Operations professionals to serve as AI data trainers. You will review structured workplace scenarios drawn from B2B SaaS IT support and access workflows and label whether specific pieces of information are appropriate for an AI agent to use and who should see them.

Labels are yes / no / undecidable. Each label requires a short, defensible justification written in clear English. You don’t need to be a developer, but you should be comfortable reading technical context and making reasoned judgments.

What You'll Do

• Review structured text scenarios based on IT support, access provisioning, onboarding/offboarding, and incident triage.
• Decide whether information is appropriate for an AI agent to use and whether it should be visible to specific people in the scenario (yes / no / undecidable).
• Write concise, defensible justifications for each label following the project’s structured rubric.
• Apply contextual-integrity norms consistently across ambiguous or incomplete scenarios.
• Work roughly 20 hours per week on a flexible schedule for about 2.5 months, completing classification, evaluation/rating, and short question-answering tasks.

Requirements

• Experience: 1+ year in IT support or IT operations at a B2B SaaS company or similar environment.
• Domain expertise: access provisioning, ticket escalation, incident triage, employee onboarding/offboarding.
• Education: any bachelor’s degree or equivalent on-the-job IT/SaaS experience.
• Tools / technical skills: familiarity with ticketing systems (for example Zendesk or Jira Service Management), IAM/IdP basics, and SaaS admin consoles; no expert coding required.
• Writing / language: strong English writing and careful reasoning; ability to produce concise, defensible justifications.
• Role-specific: high attention to detail and consistent application of structured rubrics; comfortable labeling yes/no/undecidable under contextual-integrity norms.

Who Should Apply

This project is a fit for intermediate IT support or operations professionals who want flexible, remote contract work and who enjoy making judgment calls about access, privacy, and information disclosure in B2B SaaS workflows.

You should be comfortable working independently, following rubrics closely, and explaining decisions clearly in writing.

Compensation & Logistics

Pay: $40 USD per hour. Employment type: contractor, part-time. Estimated commitment: ~20 hours per week for about 2.5 months.

Location & language: remote work for candidates based in the US, CA, GB, IE, or AU; English required. Tasks are text-based (data type: TEXT) and include classification, evaluation/rating, and question-answering labels.

How It Works

You’ll complete a short onboarding and rubric training, then begin labeling using the project’s web-based tool (OTHER labeling software). Expect sample tasks, feedback during an initial calibration period, and ongoing guidelines to maintain consistency.

Schedule is flexible—choose hours that fit your life—but you must meet quality standards and follow the project’s rubric for justifications and label consistency.