VP AI Engineering – Enterprise

This is a fully remote position, open to applicants in Florida.

📋 Description

• Define and spearhead the enterprise strategy for data and generative AI engineering.

• Develop standards, roadmaps, and operational models for analytics, machine learning, and large-scale AI implementation.

• Supervise the design, delivery, and operation of enterprise ETL/ELT platforms that integrate mainframe, SQL Server, and DB2 with cloud data and AI solutions.

• Govern feature stores, analytically optimized datasets, and data products ready for AI applications.

• Establish the enterprise direction for vectorization, embeddings, retrieval-augmented generation, and the secure consumption of data.

• Oversee the Snowflake strategy, which encompasses architecture, performance, cost governance, and integration with AWS/Azure AI.

• Collaborate with leaders in Technology, Security, Infrastructure, Legal, Risk, and Compliance.

• Set operational metrics and ensure financial discipline for investments in data and AI engineering.

• Lead engineering teams, prioritize initiatives, eliminate obstacles, and guarantee successful execution.

• Advise executive leadership on data, AI, and generative AI capabilities, associated risks, and emerging opportunities.

• Shape talent strategies, capability enhancement, and succession planning.

• Direct AI engineering initiatives for HR, Marketing, Finance, Legal, and other corporate functions.

• Identify and implement use cases involving LLM, agentic AI, workflow automation, and knowledge assistants.

• Develop reusable AI capabilities, agents, APIs, connectors, and workflow integrations.

• Administer and manage ChatGPT Enterprise and Claude.

• Oversee user management, licensing, roles, permissions, workspaces, and enterprise configurations.

• Establish approved connectors and integrations with enterprise data and applications.

• Define access controls, data-use guardrails, and standards for GPTs, agents, projects, and connectors.

• Monitor adoption rates, utilization, licensing, token/API usage, platform effectiveness, costs, risks, and business value.

• Manage expenses related to the AI platform, including forecasting, chargeback/showback, license optimization, and vendor commitments.

• Cultivate relationships with OpenAI, Anthropic, and other enterprise AI providers.

• Assess, pilot, restrict, or widely adopt new platform capabilities.

• Lead a small engineering/platform team dedicated to AI solutions, integrations, administration, and support.

• Partner with business leaders to promote responsible adoption and measurable improvements in productivity.

• Perform additional duties as assigned.

• Provide supervisory leadership, recruit team members, and conduct performance evaluations.

⛳️ Requirements

• A Bachelor’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field from an accredited college or university is required.

• A Master’s degree is preferred.

• Over 10 years of experience in engineering, platform, or enterprise technology.

• At least 5 years of experience in a technical leadership role.

• A decade of progressive experience in data engineering, analytics platforms, or AI-related technologies, including senior leadership responsibilities for enterprise-scale data or AI initiatives, or an equivalent combination of education and experience is required.

• Strong practical understanding of LLMs, agentic AI, RAG, APIs, workflow automation, and enterprise integration.

• Experience in creating AI solutions for HR, Marketing, Finance, or Legal departments.

• Proven experience in administering enterprise SaaS or AI platforms at a significant organizational scale.

• Comprehensive understanding of identity management, SSO, RBAC, connectors, APIs, data permissions, and enterprise security.

• Strong knowledge of AWS and/or Azure.

• Experience in establishing AI governance, access controls, monitoring, and responsible-use standards.

• Strong financial management skills related to technology consumption, licensing, vendor expenses, and forecasting.

• Familiarity with Snowflake and AWS/Azure ecosystems.

• Experience in machine learning, feature engineering, vector databases, and RAG-based architectures.

• Proven ability to manage large, cross-functional initiatives with significant financial and organizational impact.

• Exceptional executive communication skills.

• Capability to lead amidst ambiguity, scale new capabilities, and drive enterprise-wide change.

• Ability to meet or exceed performance competencies.

• Willingness to travel as required.

🏝️ Benefits

• Work-life balance.

• Reasonable accommodations when applicable and appropriate.

• Equal Opportunity Employer and Drug-Free Workplace.