Operational AI Strategy Manager

About This Role

LVT is looking for a strategic, hands‑on expert to own our company‑wide AI transformation. As Operational AI Strategy Manager, you will define how LVT adopts and scales AI across every function, building the models, policies, and cross‑functional partnerships that transform AI from an experiment into a competitive advantage. This senior individual‑contributor role has broad organizational reach, executive visibility, and is based at our American Fork, UT headquarters.

• Define and drive LVT’s enterprise AI adoption strategy, establishing a clear roadmap for how AI delivers business value across every department.
• Develop and own LVT’s internal AI policy framework, setting standards for responsible AI use, governance, and organizational readiness.
• Audi t and rationalize the AI capabilities embedded across LVT’s existing tech stack — driving adoption of high‑value tools, consolidating redundancies, and deprecating underutilized spend.
• Build and deploy RAG pipelines and Cortex‑based models in partnership with Data Engineering, translating business needs into production‑ready AI solutions.
• Architect the AI strategy at the intersection of automation — defining where and how AI augments workflows built on platforms like Workato and Oracle Integration Cloud (OIC).
• Design and build the AI components embedded within automation flows, partnering with the Automation Integrations team to ensure seamless, intelligent execution.
• Champion AI literacy and adoption across LVT, partnering with business leaders to identify high‑impact opportunities and drive measurable outcomes.
• Communicate AI strategy and progress to executive leadership, translating technical direction into clear business outcomes.

• Strategic and technical:
  You can write a boardroom‑ready AI strategy in the morning and build a RAG pipeline in the afternoon — you’re equally comfortable in both modes.
• AI practitioner:
  You have hands‑on experience building and deploying LLM‑based solutions, including retrieval‑augmented generation (RAG), vector databases, and model fine‑tuning or prompt engineering at scale.
• Platform fluent:
  You understand enterprise automation platforms (Workato, OIC, or equivalent) and can reason clearly about where AI fits within complex integration flows.
• Tech stack evaluator:
  You know how to assess embedded AI features across SaaS and enterprise tools — cutting through vendor marketing to determine what’s actually delivering value, what’s redundant, and what should go.
• Policy‑minded:
  You’ve developed or contributed to AI governance frameworks, usage policies, or organizational AI standards — and you understand the stakes of getting it right.
• Cross‑functional influencer:
  You build trust with engineering, operations, and executive stakeholders alike, and know how to move initiatives forward without direct authority over every team involved.
• Data‑environment comfortable:
  You’re experienced working within data platforms (e.g., Snowflake, Cortex) and partnering with data engineering teams to bring AI models from concept to production.
• Outcome‑oriented:
  You measure your work by business impact — adoption rates, efficiency gains, cost reduction — not by the sophistication of the model you shipped.

We believe you do your best work when your whole life is supported. We invest in our crew’s health, families, and financial futures with a benefits package designed to support you inside and outside the office.

All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. All candidates must pass a drug screening and background check upon employment. Some roles may also require passing a federal background check and fingerprinting. Must be authorized to work in the U.S. If reasonable accommodation is needed to participate in the job application or interview process, and/or to perform essential job functions, please reach out to your recruiter.