Job Description

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.

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