Director AI & Innovation

WORK FOR A WINNING TEAM THAT NOW OFFERS BENEFITS FROM DAY ONE

At Hilton Grand Vacations, you will become a part of a culture that encourages and motivates you toward achieving your goals.

Here’s why you will love it here:

• Recognition Programs and Rewards
• Excellent health care options, including medical, dental, and vision
• A people-first culture
• Go Hilton: Travel Discounts Program Hilton hotel rates worldwide.
• Perks at work: Employee Pricing platform
• Employee Assistance Program that supports your physical and mental well-being.
• Paid Vacation Time and Paid Sick Days
• 401(k) program with company match
• Tuition reimbursement programs
• Numerous learning and advancement opportunities
• And more!

What Will I be Doing?

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.

• 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.

To fulfill this role successfully, you must possess the following minimum qualifications and experience: