AI Product Manager

Job Title: Vice President – AI Product Manager

Location: New York, NY

Firm Overview

Cantor Fitzgerald, with over 16,000 employees, has been a leading global financial services firm at the forefront of financial and technological innovation since 1945. Cantor is a preeminent investment bank serving more than 5,000 institutional clients around the world, recognized for its strengths in fixed income and equity capital markets, investment banking, SPAC underwriting, PIPE placements, commercial real estate, and its global distribution platform.

Capitalizing on the firm’s financial acumen and technology prowess, Cantor’s portfolio of businesses also includes Prime Brokerage, Asset Management, and other businesses and ventures. Cantor operates trading desks in every major financial center globally, with offices in over 30 locations worldwide.

As one of the few remaining private partnerships on Wall Street, Cantor has the distinct ability to focus on long-term value creation and move decisively. Our structure allows us to respond quickly to client needs, develop differentiated solutions, and attract individuals who take ownership and thrive in fast-moving environments.

Responsibilities

Cantor Fitzgerald is seeking an experienced AI Product Manager to lead the strategy, development, and adoption of AI-powered products that drive business transformation across the firm. This individual will serve as the bridge between business stakeholders, technology teams, and end users, ensuring that AI initiatives deliver measurable business value while meeting regulatory and operational requirements.

The ideal candidate combines strong product management fundamentals with a deep understanding of artificial intelligence technologies, enterprise workflows, and change management practices.

Key Responsibilities

• Own and execute the product strategy, roadmap, and lifecycle for AI-enabled solutions across front-office, middle-office, and corporate functions.
• Identify high-impact business opportunities and translate them into scalable AI product initiatives aligned with firm objectives.
• Partner with engineering, data science, and platform teams to design and deliver solutions leveraging large language models (LLMs), retrieval-augmented generation (RAG), agentic workflows, automation technologies, and advanced analytics.
• Define product requirements, success metrics, user journeys, and release plans while balancing business priorities, technical constraints, and compliance considerations.
• Lead discovery efforts with business leaders and end users to understand pain points, validate use cases, and prioritize opportunities.
• Drive the adoption and utilization of AI capabilities through stakeholder engagement, training, communication, and change management initiatives.
• Establish frameworks for measuring business impact, including productivity gains, user adoption, process efficiency, risk reduction, and return on investment.
• Collaborate with Legal, Compliance, Risk, and Information Security teams to ensure AI products are developed and deployed responsibly within governance standards.
• Monitor emerging AI technologies, industry trends, and competitive developments to identify new opportunities and maintain strategic advantage.
• Act as a trusted advisor to senior leadership regarding AI strategy, product investment decisions, and capability development.
• Manage product backlogs, prioritization processes, and cross-functional dependencies to ensure timely delivery of initiatives.
• Champion a user-centric, data-driven approach to product development and continuous improvement.

Qualifications

Professional Qualifications & Experience

• 7+ years of product management, technology, digital transformation, or related experience, with at least 3 years focused on AI, machine learning, data products, or intelligent automation solutions.
• Proven track record of launching and scaling enterprise technology products from concept through adoption and optimization.
• Strong understanding of AI and LLM technologies, including prompt engineering, RAG architectures, vector databases, agent frameworks, model evaluation, and AI governance considerations.
• Experience defining product roadmaps, business cases, KPIs, and go-to-market strategies for enterprise solutions.
• Ability to partner effectively with software engineers, data scientists, architects, and business stakeholders across multiple functions.
• Experience …