AI MARKETING PROJECT MANAGER

Job Title: AI MARKETING PROJECT MANAGER
Job Location:
New York, NY
Job Type: Contract
Job Description:
Develop, communicate, and maintain integrated project and portfolio plans, including scope, milestones, dependencies, resourcing, decision points, and delivery risks. Coordinate cross-functional teams across business, architecture, engineering, data, testing, security, vendors, and offshore / distributed delivery resources throughout the project life cycle.

Establish clear accountability for each initiative, confirm responsibilities, track commitments, and hold team members and partners accountable for agreed deliverables. Partner with Marketing Owners to clarify the business problem, define requirements, establish acceptance criteria, secure sign-off, and maintain alignment to expected outcomes and KPIs. Manage critical dependencies, especially data quality and readiness, platform integration, workflow simplification, architecture, and availability of subject-matter experts.

Drive responsible AI delivery by ensuring human-in-the-loop checkpoints and incorporating brand, legal, compliance, privacy, security, and governance requirements into workflows before deployment. Oversee pilots, proofs of concept, testing, release readiness, implementation, and transition to sustainable operating support; ensure build and system documentation is complete. Lead adoption and change-management activities, including communications, training, champion engagement, feedback loops, and measurement of user adoption and business impact.

Monitor progress through regular status meetings and insightful reporting; communicate status, decisions, risks, issues, and required escalations to sponsors and stakeholders. Facilitate gateway reviews for business-critical initiatives and make sure decisions, assumptions, actions, and approvals are documented and traceable. Measures of Success
Priority AI initiatives have clear scope, owners, milestones, dependencies, acceptance criteria, and measurable KPIs. Delivery progresses predictably from activation and scoping through build, pilot, proof, and operational handoff.

Risks, issues, data gaps, resource constraints, and cross-team dependencies are identified early and resolved or escalated decisively. AI solutions are adopted responsibly, with human oversight, documented controls, strong stakeholder confidence, and appropriate support readiness.