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Onsite role || AI Project Manager with Insurance Domain || NYC, NY

HAN IT Staffing Inc.New York, NY🇺🇸United StatesPosted 21 Aug 2026

Why This Role Stands Out

This on-site AI Project Manager role offers an exciting opportunity to drive impactful AI initiatives within the insurance sector, perfect for a mid-senior professional with a strong understanding of the AI lifecycle and excellent leadership skills. You will bridge business and technical teams, ensuring the successful delivery of cutting-edge AI solutions and shaping the future of data-driven decision-making.

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
New York, NY, United States
Posted
Yesterday
Risk AssessmentStakeholder Management

Job Description

Role: AI Project Manager (Insurance domain exp)

Location: NYC NY 5 Days Onsite

Duration: Long-term Contract

Job Description:

AI Project Manager Job Description: An AI Project Manager oversees AI/ML projects from ideation to deployment, bridging business goals, technical teams (e.g., data scientists, engineers), and stakeholders to deliver on time, within budget, and with high impact. 

Key Responsibilities:

Project Planning & Execution: Define scope, goals, timelines, budgets, milestones, and resource allocation; monitor progress, risks, and performance metrics.

Technical Oversight: Understand AI concepts, lifecycle (data prep, model training/deployment, monitoring); manage data readiness, model evaluation, and AI integration with existing systems.

Team & Stakeholder Management: Lead cross-functional teams; communicate requirements, set expectations, and align data engineering, AI, and business priorities.AI-Specific Duties: Integrate AI tools for scheduling/risk assessment; ensure ethical AI, data privacy, regulatory compliance, and post-project evaluations. Strategic Elements: Prioritize initiatives, develop AI roadmaps, mitigate risks, and drive business value through data-driven decisions. & nbsp;

Required Skills & Qualifications Core Skills: Data literacy, analytical thinking, AI lifecycle knowledge (e.g., CPMAI methodology), critical problem-solving, communication, and adaptability to AI changes.

Technical Proficiency: Familiarity with AI tools, version control, and project management software supporting data workflows.

Education/Experience: Bachelor's in Computer Science, Data Science, Engineering, or related; experience in AI/ML projects.

Soft Skills: Leadership, stakeholder relationship-building, ethical awareness.

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