AVP/VP, AI Transformations Manager
Listed on 2025-12-02
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IT/Tech
AI Engineer, Data Science Manager, Data Security, Business Systems/ Tech Analyst
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Who We Are
Cross River is a highly profitable, fast-growing financial technology company powering the future of financial services. Our comprehensive suite of innovative and scalable embedded payments, cards, and lending products deliver financial services for millions of businesses and consumers around the globe. Cross River is backed by leading investors and serves the world’s most essential fintech and technology companies. Together with its partners, Cross River is reshaping global finance and financial inclusion.
We're Looking For
The AI Transformation Manager reports to the Chief Data and AI Officer and plays a critical role in driving Cross River’s AI-led transformation and commercialization strategy. This position is responsible for orchestrating the end-to-end implementation of AI initiatives across the enterprise—bridging strategy, productization, compliance, and delivery to ensure measurable business impact. The ideal candidate combines deep expertise in AI/ML program management with a pragmatic understanding of financial services and regulatory environments.
Responsibilities- Define and manage the AI Transformation roadmap, ensuring alignment with Cross River’s strategic objectives, regulatory standards, and innovation priorities.
- Partner with business, data, and technology leaders to identify AI-driven opportunities for efficiency, risk management, and new revenue models.
- Establish a governance framework for AI projects, including evaluation metrics, responsible AI principles, and lifecycle management.
- Oversee commercialization of AI capabilities, enabling scalable deployment of internal tools and potential external monetization opportunities.
- Lead the planning, coordination, and execution of AI initiatives across multiple business domains—banking, lending, risk, compliance, and customer experience.
- Develop and maintain a portfolio management system for all AI programs, ensuring transparency on timelines, costs, dependencies, and outcomes.
- Ensure data readiness and model governance across all AI deployments in close partnership with data engineering and compliance teams.
- Track and report on transformation metrics, including adoption, ROI, and productivity gains.
- Partner with product, engineering, operations, and risk teams to embed AI solutions into enterprise workflows.
- Drive organizational change management to enable smooth adoption of AI technologies, ensuring training and alignment across teams.
- Serve as a liaison between business and technical teams, translating complex AI capabilities into actionable business insights.
- Promote a culture of responsible AI innovation that balances experimentation with ethical standards and risk management.
- Identify opportunities to externalize AI capabilities through partnerships, APIs, and new product lines.
- Collaborate with external vendors, startups, and research organizations to expand the bank’s AI ecosystem.
- Support the Chief Data and AI Officer in defining AI monetization strategies and evaluating go-to-market models.
- 10+ years of experience in technology, analytics, or transformation roles, with at least 5 years in AI/ML program or product management.
- Proven experience leading cross-functional AI initiatives from conception through implementation in a regulated industry (preferably financial services, fintech, or banking).
- Strong understanding of AI platforms, MLOps, model governance, and data management frameworks.
- Experience managing stakeholder engagement, budgets, and vendor relationships for large-scale transformation programs.
- Exceptional ability to translate technical AI concepts into business outcomes and communicate effectively at all organizational levels.
- Master’s degree in Business, Data Science, Engineering, or a related field.
- Prior experience applying AI solutions in regulated environments, such as banking, healthcare, or insurance.
- Familiarity with AI governance, including bias mitigation, interpretability, and model monitoring.
- Experience in…
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