Vice President, Artificial Intelligence & Data
Overview
Patrick Industries, a publicly traded company headquartered in Elkhart, Indiana, seeks an experienced executive to lead its enterprise AI and data capability. Reporting to the Chief Information Officer, the Vice President of AI & Data will oversee the development and scaling of AI and data initiatives, setting the strategy, governance, and delivery model.
Responsibilities
Own the enterprise AI and data strategy and roadmap, the multi-year investment plan and budget allocation, the operating model and decision rights, and an outcome thesis tied to defined value levers.
Own data governance — ownership and stewardship, quality, master data management, access, and lineage — alongside acceptable-use policy, an approved-tool catalog with exception workflow, security/model/vendor risk, and a controls library and risk register.
Prioritize, sequence, and stage-gate the portfolio; control scope, budget, and resources; manage cadence, milestones, and dependencies; and track value realization and benefits.
Build AI and data literacy from the executive team to the frontline, role-based training paths, change and communications plans, and a champion network that drives durable adoption.
Own the data foundation AI depends on — the lakehouse/fabric bridging 40+ ERPs, the semantic layer, master data management and entity matching, cataloging, and observability — and sequence AI delivery behind data readiness.
Own the roadmap for shared LLMs, agents, APIs, and utilities, with monitoring, observability, evaluation, and quality controls, plus utilization analytics, financials, and vendor management.
Ensure every production solution has a named owner, a managed backlog and release plan, KPI ownership and user-feedback loops, and disciplined reuse, consolidation, and sunset decisions.
Set reference architecture, integration patterns, and standards; run SDLC, DevOps, and CI/CD for AI workloads; manage environments, infrastructure-as-code, and reliability (SRE); and own production support and incident response.
Own curated knowledge bases and sources of truth, content lifecycle and access controls, retrieval infrastructure, and data-quality stewardship with ongoing SME-driven curation.
Recruit and scale a dedicated team from a small founding core to roughly twenty professionals over three years — solution architecture, AI/ML and software engineering, data engineering and architecture, DevOps/MLOps, product management, and data and solution governance — operating a lean internal model that orchestrates strategic delivery partners and brand adoption rather than depending on them.
Maintain an active scan of frontier models, agentic frameworks, and tooling with a disciplined evaluation pipeline that separates durable capability from hype, keeping the approved-tool catalog and reference patterns current without compromising security or governance.
Translate emerging capability into pragmatic roadmap and investment decisions, and continuously upskill the team so Patrick’s practice compounds rather than ages.
Qualifications
Proven executive leadership in AI, data, automation, advanced analytics, or digital product delivery, with a track record of taking solutions from pilot to enterprise scale.
Strategic command of AI and data investment — able to shape a multi-year roadmap and budget, prioritize for ROI, and make disciplined build / buy / partner decisions.
Deep experience with modern data platforms and governance (lakehouse/fabric, MDM, cataloging, data quality and lineage) and the modern AI stack (LLMs and agentic systems, RAG, MLOps/LLMOps, cloud) — with the habit of staying at the frontier.
Strong experience operating DevOps and agile delivery at enterprise scale, with a disciplined, metrics-driven delivery capability.
Experience leading within federated or decentralized business environments and influencing senior business stakeholders.
Deep understanding of enterprise governance disciplines — security, data, architecture, and compliance — and executive communication skills suited to C-suite and Board engagement.
A builder who thrives in a relatively undefined, zero-to-one environment and is energized by standing up a team, a platform, and an operating model.
Leadership Competencies
Executing for Results
Leading
Relationships & Influence
Candidate Profile
The ideal candidate will have:
Proven executive leadership in AI, data, automation, advanced analytics, or digital product delivery, with a track record of taking solutions from pilot to enterprise scale.
Strategic command of AI and data investment — able to shape a multi-year roadmap and budget, prioritize for ROI, and make disciplined build / buy / partner decisions.
Deep experience with modern data platforms and governance (lakehouse/fabric, MDM, cataloging, data quality and lineage) and the modern AI stack (LLMs and agentic systems, RAG, MLOps/LLMOps, cloud) — with the habit of staying at the frontier.
Strong experience operating DevOps and agile delivery at enterprise scale, with a disciplined, metrics-driven delivery capability.
Experience leading within federated or decentralized business environments and influencing senior business stakeholders.
Deep understanding of enterprise governance disciplines — security, data, architecture, and compliance — and executive communication skills suited to C-suite and Board engagement.
A builder who thrives in a relatively undefined, zero-to-one environment and is energized by standing up a team, a platform, and an operating model.