QTS Data Centers
Director, Enterprise AI Enablement
Suwanee, GA · Director
Sponsorship not specifiedDetected 5 days ago
LLMsLeadershipCommunication
About the role
- QTS is powered by people, and this role exists to make AI powerful for them - turning sanctioned tools like Microsoft 365 Copilot and the applications built by the Business AI Delivery team into confident, everyday productivity.
- This leader also is critical to influencing the backbone of QTS' AI Architecture and Coordination, and embeds the QTS operating principles - be creative, trust your data, and govern from day one - into how the company adopts AI.
Requirements
- Bachelor's degree in a relevant field, or equivalent professional experience.
- Demonstrated ability to set strategy
Nice to have
- Familiarity with responsible-AI / AI-governance frameworks (e.g., NIST AI RMF) and enterprise data-privacy and security considerations.
- Experience leading enablement across multiple geographies, including the U.S. and Europe.
- Experience in a data center, critical-facilities, or technology-operations environment.
- We conform to all the laws, statutes, and regulations concerning equal employment opportunities and affirmative action.
- We strongly encourage women, minorities, individuals with disabilities and veterans to apply to all of our job openings.
- The "Know Your Rights" Poster is included here:
- Know Your Rights (English)
- Know Your Rights (Spanish)
Skills
- Replace shadow AI with safe, sanctioned tools, and embed responsible-AI guardrails into every enablement program.
- Other duties as assigned.
Equal opportunity
- QTS is committed to working with and providing reasonable accommodations to individuals with disabilities.
- If you need a reasonable accommodation because of a disability for any part of the employment process, please send an e-mail to talentacquisition@qtsdatacenters.com and let us know the nature of your request and your contact information.
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This listing is sourced directly from QTS Data Centers's careers page and normalized into a canonical job model.