Director AI & Innovation

Hilton Grand Vacations•Orlando, FL

About The Position

HGV is looking for a senior AI and Innovation leader who turns AI from a portfolio of projects into a governed, scalable enterprise capability while providing deep hands-on technical leadership across applied AI, software engineering, cloud infrastructure, data platforms, and production deployment. This leader owns innovations research, strategy, platform direction, operating model, governance, talent, vendor strategy, and delivery execution, with a strong emphasis on practical engineering judgment and measurable business outcomes. This is intentionally a hands-on technical leadership role: expected to guide architecture reviews, evaluate emerging AI capabilities, shape platform and infrastructure decisions, lead technical experimentation and prototyping, challenge vendors and internal teams on implementation tradeoffs, and ensure promising AI concepts/innovations move from feasibility and proof of concept into secure, reliable, observable, and supportable production solutions. Under the direction of the Senior Director of Sports Marketing & Sponsorships, the Director is responsible for executing best-in-class sports marketing and sponsorship initiatives that drive brand awareness, partner value, and revenue growth. This role plays a critical part in delivering high-impact events, managing sponsorship relationships, and supporting strategic initiatives across the sports and experiential marketing portfolio. The Director leads day-to-day execution across key partnerships, events, and activations while ensuring alignment with the broader sponsorship strategy and organizational goals.

Requirements

10+ years of engineering leadership, including proven delivery of production AI systems and managing cross-functional organizations
Strong knowledge of cloud (Azure, Databricks), AI architecture, security, and data platforms
Strong commercial, budgeting, and vendor-management skills; demonstrated ability to drive organizational change.
BA/BS/Bachelor's Degree

Nice To Haves

Experience in hospitality, travel, or another high-volume, real-time pricing/inventory business.
Experience with agentic AI platforms, knowledge graphs, or conversational AI in production
Familiar with the Patent Process from concept to actual patent submissions. This includes realization of a novel idea
MS/MA/Master's Degree /Ph.D.

Responsibilities

Define and execute enterprise AI strategy and the multi-year roadmap; align AI investment with business outcomes and ROI; own the AI capital program, including intake, prioritization, lifecycle governance, and value measurement.
Provide hands-on technical leadership across applied AI, software engineering, APIs, data systems, cloud infrastructure, AI platforms, MLOps/LLMOps, deployment pipelines, testing, observability, reliability, security, and production support models.
Lead evaluation, research, and rapid prototyping of emerging AI capabilities, including generative AI, agentic systems, machine learning, retrieval-based systems, intelligent automation, and other evolving technologies; assess feasibility, business value, operational risk, and production readiness.
Work within and improve a disciplined research-to-production lifecycle that moves concepts through feasibility assessment, proof of concept, prototype, pilot, production deployment, measurement, and continuous improvement.
Set standards for models, agents, inference platforms, MLOps/LLMOps, prompt and retrieval quality, benchmarking, model evaluation, latency, reliability, explainability, cost management, security, and responsible AI practices.
Drive technical architecture decisions across cloud, data, AI infrastructure, model-access patterns, integration approaches, and deployment environments; make build-vs-buy recommendations grounded in technical evaluation, vendor due diligence, cost, risk, and long-term maintainability.
Deliver with AI governance team that includes setting standards, cost, and platform foundation: model approval, risk, audit, compliance standards, data protection, monitoring, and operational controls. Partner with Legal, Security, Risk, Privacy, and Data Governance to embed responsible AI practices across programs.
Guide teams and stakeholders in determining when business problems are best solved through generative AI, predictive ML, rules/workflow automation, analytics, improved data foundations, or process redesign.
Own portfolio prioritization and delivery frameworks, establish operating cadence, track adoption and business value, and remove organizational barriers to AI adoption.
Build and lead AI Engineering and Applied AI capabilities plus contractor/vendor pods; define hiring strategy, technical standards, career frameworks, and AI literacy programs across the organization.
Act as the primary AI advisor to executive leadership: communicate opportunity, risk, technical tradeoffs, investment needs, delivery implications, and business cases in clear, evidence-based terms.