VP AI Engineering - Enterprise
Listed on 2026-10-13
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IT/Tech
AI Engineer (Applied/Software)
Telecommuter FL
R79028
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VP AI Engineering - Enterprise
PRIMARYPURPOSE:
The Vice President, Generative (Gen) AI Engineering Enterprise, provides executive leadership, strategic direction, and accountability for the enterprise data and AI engineering ecosystem that enables the organization’s most advanced analytics, data science, and generative AI initiatives. This role owns the vision, governance, and execution model for the enterprise data supply chain that powers machine learning platforms, feature stores, and production‑grade generative AI capabilities.
As a senior leader, the Vice President establishes and scales the engineering strategy required to transform legacy and modern data assets into trusted, AI‑ready enterprise capabilities. The role ensures that data and AI engineering investments are aligned to business outcomes, regulatory expectations, and long‑term architectural sustainability across on‑premise and multi‑cloud environments, including Snowflake and AWS/Azure AI ecosystems.
ESSENTIAL FUNCTIONS AND RESPONSIBILITIES- Defines and leads the enterprise strategy for data and generative AI engineering, establishing standards, roadmaps, and operating models that support analytics, machine learning, and AI at scale.
- Provides executive oversight for the design, delivery, and operation of enterprise ETL/ELT platforms that integrate legacy on‑premise systems (including mainframe, SQL Server, and DB2) with modern cloud data and AI platforms.
- Establishes governance and accountability for feature stores, analytically optimized datasets, and AI‑ready data products to ensure reproducibility, regulatory compliance, and production reliability.
- Sets direction for generative AI enablement, including enterprise approaches for vectorization, embeddings, retrieval‑augmented generation (RAG), and secure consumption of structured and unstructured data.
- Owns the enterprise Snowflake strategy, including architectural patterns, performance standards, cost governance, and integration with cloud‑based AI services across AWS and Azure.
- Leads cross‑functional collaboration with Technology, Security, Infrastructure, Legal, Risk, and Compliance leaders to ensure data and AI engineering practices meet security, privacy, and regulatory requirements.
- Establishes executive‑level operating metrics and financial discipline to ensure data and AI engineering investments deliver measurable business value and return on investment.
- Provides leadership and direction to engineering leaders and teams, setting priorities, removing organizational barriers, and ensuring consistent execution across portfolios and initiatives.
- Serves as a senior advisor to executive leadership on data, AI, and generative AI capabilities, risks, and opportunities, translating technical complexity into business‑level insights and decisions.
- Drives organizational readiness by shaping talent strategy, capability development, and succession planning for data and AI engineering roles across the enterprise.
- Job Responsibilities
- Lead AI engineering for enterprise functions including HR, Marketing, Finance, Legal, and other corporate functions.
- Identify and deliver high‑value LLM, agentic AI, workflow automation, and knowledge‑assistant use cases.
- Build reusable AI…
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