Project Lead, AI Transformation & Enablement

RXR•New York, NY

8d•$120,000 - $130,000•Onsite

About The Position

Project Lead, AI Transformation & Enablement is a cornerstone role within RXR’s AI-First transformation, embedding AI into the daily fabric of how our teams operate. Acting as translator, architect, and orchestrator, this person partners with business units to assess current processes, identifies opportunities for automation and augmentation, builds AI solutions that deliver measurable value, and monitors ongoing adoption, operationalization, and value measurement. This role requires proficiency with enterprise AI platforms (such as ChatGPT and other no/low-code automation tools), the ability to design and prototype human-centered AI workflows, expertise in structured problem framing, prompt design, and responsible AI practices, and experience in transformative change management with non-technical stakeholders.

Requirements

AI Fluency: Strong understanding of AI platforms (e.g., ChatGPT), prompt engineering, and a broad and diverse background of experimentation with automation tools.
Responsible AI Judgment: Awareness of fairness, risk, and governance implications in AI deployment.
Human-Centered Design: Understanding of how users build trust in systems. Ability to discern between functional and cognitive user needs and translate them into clear, intuitive interfaces that support efficient, accurate, and trustworthy user interaction with digital and AI-enabled systems.
Business Translation: Ability to convert business goals into AI opportunities through structured scoping frameworks.
Structured Problem Solving & Translation: Ability to clarify ambiguous goals into testable system requirements.
Stakeholder Leadership & Facilitation: Ability to run structured working sessions, manage tradeoffs, align decision-makers, and drive decisions under ambiguity.
Workflow Design: Skilled in process mapping, automation design, and user-centric prototyping.
Prompt & Specification Writing: Ability to develop clear, structured prompts, scenarios, and requirements.
Change Leadership: Clear communicator who can drive adoption among nontechnical users.
ROI & Impact Orientation: Comfortable with KPI definition, data collection, and value realization analysis.
Bachelor’s degree strongly preferred; quantitative field of study preferred. Advanced certification or training in AI or automation is helpful.
3–5 years in management consulting, technology consulting, digital/automation/AI transformation, or other similar roles.

Nice To Haves

User-interface design expertise a plus.
Product management experience a plus.
Real estate, finance, or construction experience a plus.

Responsibilities

Conduct structured workflow audits with key business unit stakeholders using a problem-first canvas, mapping current-state processes to identify inefficiencies, decision points, and human-in-the-loop needs.
Translate ambiguous business objectives into clear problem statements, system requirements, and success metrics (such as opportunity size, ROI, and level of effort).
Maintain an intake pipeline of AI opportunities; evaluate and prioritize using a standardized scoring framework (impact, effort, risk, adoption readiness).
Define criteria for measuring the success of prioritized use cases (both pilot and post-deployment).
Design AI-first future-state processes for these prioritized use cases and validate with key business unit stakeholders. Determine ability to build these processes using no-code/low-code workflows (e.g., ChatGPT Enterprise paired with MCP servers) or if custom code built by the software & data engineering team is required.
For no-code/low-code prioritized use cases, build prototype use cases by developing structured prompts and scenario tests (clearly defining context, inputs, outputs, constraints) to validate via proof-of-concept. For custom code prioritized use cases, work with software & data engineering team to design specifications.
Pressure-test and iteratively refine pilots into final deliverables with business leads to ensure reliability, accuracy, and “last-mile” integration into daily operations.
Measure post-deployment impact through a clear ROI methodology, partnering with finance and business leads to quantify time savings, cost avoidance, risk reduction, or efficiency gains.
Identify trends, gaps, and issues in results to continuously improve how AI workflows operate.
Report regularly to the AI Advisory Council on performance, adoption, and value creation.
Act as an AI evangelist, leading live demos, workshops, and user testing sessions to help teams understand how, why, and when to use AI.
Identify and mentor departmental AI Champions as part of RXR’s hub-and-spoke AI model.
Develop and maintain process documentation, prompt libraries, and training content as part of RXR’s AI Acumen Program.
Collect user feedback and adoption data to ensure all efforts are optimized.
Ensure alignment with RXR’s standards of Responsible AI and Governance.