Interstates

Interstates

BICSI Certified Trainer (CT)

Omaha, NE

Sponsorship not specifiedDetected 26 days ago
TypeScriptComplianceLeadershipCommunicationMentoring

About the role

  • From our headquarters in Iowa to job sites across the country, we're doing award-winning electrical, controls, automation, and OT work that powers industrial facilities for clients here in the U.S. and around the world.
  • If you want to grow and do meaningful work, you'll feel at home here.
  • After years in the field, you've earned more than experience - you've earned knowledge worth passing on.

Responsibilities

  • Deliver BICSI curriculum in accordance with BICSI standards
  • Lead classroom instruction, hands-on labs, and student evaluations
  • Support BICSI audits, site visits, and continuous improvement efforts

Requirements

  • BICSI authorized (CT) status, or ability to obtain
  • 5-7+ years of structured cabling or ICT field experience
  • Advanced knowledge of copper and fiber systems, testing, and troubleshooting
  • Experience teaching in a BICSI Authorized Training Facility (ATF)
  • Experience supporting BICSI ATF audits
  • Familiarity with industry test platforms (Fluke, VIAVI, EXFO, etc.)
  • Benefits You Can Depend On:
  • Maintain required training records, attendance, and documentation
  • Current BICSI Technician certification in good standing
  • Strong communication and facilitation skills for adult learners
  • Additional BICSI credentials (RCDD, RTPM, DCDC, OPS etc.)
  • Field leadership or supervisory experience

Benefits

  • Bonus incentives
  • Health, Vision, and Dental Insurance
  • PTO and Holiday Pay
  • Disability and Life Insurance
  • Parental Leave

Company info

  • Interstates may collect personal information as part of your job application, such as your contact details, work history, education, and any information you provide.

Equal opportunity

  • Interstates is an EEO provider and offers a drug-free workplace.

This listing is sourced directly from Interstates's careers page and normalized into a canonical job model.