Senior Director - AI Enablement

ABOUT GREYSTAR

Greystar is a leading, fully integrated global real estate platform offering expertise in property management, investment management, development, and construction services in institutional-quality rental housing. Headquartered in Charleston, South Carolina, Greystar manages and operates over $350 billion of real estate in more than 260 markets globally with offices throughout North America, Europe, South America, and the Asia-Pacific region. Greystar is the largest operator of apartments in the United States, managing over one million units/beds globally. Across its platforms, Greystar has nearly $79 billion of assets under management, including over $34 billion of development assets and over $36.5 billion of regulatory assets under management. Greystar was founded by Bob Faith in 1993 to become a provider of world-class service in the rental residential real estate business. To learn more, visit www.greystar.com .

JOB DESCRIPTION SUMMARY

The Senior Director, AI Enablement owns the production of role-specific AI capability: the Skills, projects, agents, product education and workflows that make GPS, Prism and our data platform usable inside the job, for the roles that matter most. Training is a delivery mechanism for this work, not the product. The product is a working set of content and tools a Greystar team member can pick up and use, on real Greystar data, and a measurable change in how they operate.

This is the technical counterpart to the Director, Talent Development in People & Culture. That role owns the enterprise learning framework, leadership development and the learning technology stack, and is the distribution channel to the workforce. This role owns what gets distributed — the artifacts, the technical standards behind them, and the adoption they drive.

This is a builder’s seat with a leader’s remit. The right person is fluent enough in Claude, ChatGPT, AI tools, MCP and data platforms to author skills personally and set the bar for a team that does, and commercial enough to argue, in NOI terms, why a given workflow should be rebuilt at all.

JOB DESCRIPTION

Key Responsibilities

Role-Based Capability Production

Define, for each priority role, what “AI-enabled” concretely means in the workflow — which decisions, which reports, which repetitive steps — and build the artifacts, or work with the teams to build the artifacts and education that deliver it.

Author and ship Skills, projects and agent workflows grounded in Greystar’s metric definitions (Atlas), data platform (DMP) and intelligence products (GPS, Prism, LEAP); personally build the first versions, then scale the team’s output working closely with your HR counterpart to expand delivery.

Maintain a governed skill & tool library with ownership, versioning, test cases and deprecation — treated as a product, not a training catalogue.

Sequence work by leverage: key roles first, in lockstep with leadership, the GPS roadmap and the FDI Pod deployments.

Adoption and Measurement

Own the adoption metric for AI capability across eligible roles: active users, repeat usage, workflow coverage, time-to-first-value.

Instrument enablement artifacts so usage is visible without self-report; partner with Data Engineering on the consumption and usage feeds.

Run the feedback loop from the field into the artifacts — what breaks, what is ignored, what gets copied — and iterate weekly.

Report adoption alongside FDI Pod impact so cost and value are always shown together.

Partnership with People & Culture

Serve as the primary technical partner to the Director, Talent Development, and to People Strategy & Programs on AI readiness; P&C owns the pathway, readiness approach and competency framework, and this role owns the technical content and the tools.

Feed enablement artifacts and technical curriculum into Workday Learning and P&C programs as the distribution channel; do not build a parallel LMS.

Share role-level adoption data (active users, workflow coverage, time-to-first-value) with People Strategy & Programs so manager enablement and communications can target where readiness lags.

Jointly define what an “AI-ready” role profile looks like for hiring and internal mobility, with P&C owning the competency framework.

Standards, Safety and Governance

Set the technical standards for enablement artifacts: data access aligned to the External Data Sharing Framework and Unity Catalog permissions; no ungoverned data paths.

Ensure every skill is grounded in the definition of record (Atlas/GPS); when a skill and a legacy report disagree, the platform number travels.

Partner with InfoSec on prompt, data and model-flexibility standards as the model landscape changes.

Team Leadership

Lead and retool the AI Enablement team from a training orientation to a build orientation; hire for skill authorship and applied AI over instructional design where the two conflict.

Build a champion network inside the business units that extends the team without adding headcount, with clear standards for what champions may and may not ship.

Model the operating principle of the function: narrow aperture, ship, measure, iterate; say no to requests without a role, a workflow and a metric attached.

What We’re Looking For

Experience

Led an AI or technology enablement function in a large, complex organization through an actual adoption curve — not a pilot program.

Demonstrated hands-on record building with LLM tooling in production: skills, prompt systems, agent workflows or equivalent that other people used at scale.

Partnered closely with data or engineering teams to ground enablement in real systems and real data, and with HR or L&D as the distribution partner.

Measured adoption and outcomes rigorously and can distinguish reach, adoption and impact without prompting.

Experience in operations-heavy, distributed businesses (real estate, financial services, healthcare, logistics) is an advantage; multifamily is not required.

Skills and Capabilities

Technically credible: comfortable in Claude Enterprise / API, MCP, prompt and skill design, and reading a data model. Can build a working skill against a governed dataset without an engineer.

Commercially literal: connects an enablement artifact to a line in the P&L (NOI, hours, CAC) or does not build it.

Product discipline: treats skills as versioned, owned, tested artifacts with users, not as course materials.

Strong influencing across functions and levels; holds a boundary with HR and the business without creating friction.

Clear, concise communicator to a senior founder-led audience; candid about what is not working.

Comfortable in ambiguity, building structure where none exists, and abandoning it when it stops working

The salary range for this position is $180,000 - $200,000 USD Annually.

Additional Compensation :

Many factors go into determining employee pay within the posted range including business requirements, prior experience, current skills and geographical location.

• •Corporate Positions : In addition to the base salary, this role may be eligible to participate in a quarterly or annual bonus program based on individual and company performance.
• •Onsite Property Positions : In addition to the base salary, this role may be eligible to participate in weekly, monthly, and/or quarterly bonus programs.

Robust Benefits Offered*:

• •Competitive Medical, Dental, Vision, and Disability & Life insurance benefits. Low (free basic) employee Medical costs for employee-only coverage.
• •Generous Paid Time off. All new hires start with 15 days of vacation, 4 personal days, 10 sick days, and 11 paid holidays. Plus your birthday off after 1 year of service! Additional vacation accrued with tenure.
• •For onsite team members, onsite housing discount at Greystar-managed communities are available subject to discount and unit availability.
• •6-Week Paid Sabbatical after 10 years of service (and