Director, Enterprise Artificial Intelligence (AI)

Interface is a global flooring and sustainability leader dedicated to rethinking how spaces work for people and the planet. Our portfolio includes Interface carpet tile and LVT nora rubber flooring and FLOR premium area rugs. Across every brand we innovate in a way that combines design performance and sustainabilitywithout compromise.

Trusted by architects designers and building professionals worldwide we help bring bold visions to life with solutions that deliver real measurable impact. Building on more than 30 years of sustainability progress and industryfirst innovation we remain all in on our goal of becoming carbon negative by 2040 without the use of offsets.

The Director Enterprise Artificial Intelligence (AI) is responsible for driving the execution of Interfaces enterprise AI strategytranslating vision into scalable secure and value-generating solutions across commercial and corporate functions.

This role serves as the bridge between business leaders technology teams and strategic partners to identify prioritize and deliver AI use cases that improve decision-making accelerate growth and increase operational efficiencywhile ensuring strong governance security and ethical use of AI.

The role will act as Interfaces AI execution leader owning delivery adoption and measurable outcomes not experimentation in isolation.

Key Responsibilities:

AI Strategy Execution & Delivery

Execute Interfaces enterprise AI roadmap aligned to company strategy digital priorities and value creation goals.
Translate strategic AI priorities into clearly defined programs use cases and roadmaps with measurable business outcomes.
Lead delivery of AI initiatives across domains and functions.
Provides Project Management services for the key AI projects.

Use Case Identification & Business Partnership

Partner with senior business leaders to identify vet and prioritize high-impact AI opportunities.
Drive structured use case intake value assessment and sequencing to ensure focus on ROI-driven outcomes.
Serve as a trusted advisor to business teams on where and how AI can responsibly accelerate results.

AI Architecture

Define and lead the enterprise AI architecture strategy establishing scalable secure and reusable AI platforms services and integration patterns
Design and govern the enterprise AI ecosystem including large language models (LLMs) AI agents knowledge platforms data foundations vector databases orchestration frameworks APIs and cloud AI services
Architect enterprise data and knowledge foundations for AI including data pipelines metadata semantic layers retrieval-augmented generation (RAG) knowledge management and data quality controls required to deliver trusted AI outcomes.
Drive AI technology standards and solution architecture reviews evaluating emerging AI capabilities platforms vendors and reference architectures while ensuring interoperability scalability reliability and operational excellence across the enterprise

Governance Risk & Responsible AI

Lead AI governance in partnership with Security Legal Privacy and Compliance teams.
Ensure AI solutions align with Interface standards for:
- Data privacy and security
- Ethical and responsible AI use

- Model transparency and explainability
Establish guardrails patterns and standards for internal and vendor-provided AI solutions.

Technology & Partner Management

Leverage strategic platforms and partners (e.g. Microsoft Salesforce Adobe Workday others) to accelerate AI adoption.
Evaluate third-party AI tools and embedded AI capabilities with a buy vs. build mindset.
Collaborate with Enterprise Architecture and Engineering teams to ensure scalability interoperability and long-term viability.
Define and track adoption usage and value realization metrics.

Team Leadership & Operating Model

Lead and mentor a small high-impact AI delivery team (internal and/or hybrid with partners).
Establish a lean operating model focused on rapid iteration business outcomes and continuous improvement.
Influence without authority across global matrixed teams.

Required Qualifications:
Bachelors degree in computer science Engineering Business or related field; Masters preferred.
812 years of experience across digital analytics AI or advanced technology roles.
Proven experience leading enterprise AI or advanced analytics initiatives from concept through production.
Strong understanding of:
- Applied AI / machine learning concepts (not pure research)
- Data platforms cloud ecosystems and modern enterprise architectures
- AI risks related to privacy security bias and compliance
Demonstrated ability to partner with senior business leaders and influence outcomes.
Experience operating in a global matrixed organization.

Preferred Experience:
Experience deploying AI solutions leveraging hyperscales (e.g. Microsoft Azure AI / Google Cloud)
Background in manufacturing industrial supply chain or commercial B2B environments.
Exposure to embedded AI within enterprise platforms (CRM ERP productivity tools).
Experience establishing AI governance frameworks or centers of enablement

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