Overview
In this role you lead the end-to-end delivery of AI-driven digital solutions, shaping the product vision and backlog to maximize value. You collaborate with customers, data scientists, and cross-functional teams to translate needs into features and model-driven capabilities. You will navigate the challenges of agentic AI, balancing business aims, technical feasibility, and model performance in a global, outcome-focused environment. This position offers a chance to influence AI governance and responsible AI practices while driving iterative value delivery.
Pay / Benefits
- hybrid work option
- annual leave
- tuition reimbursement
- referral bonuses
- success-sharing/bonus plans
- competitive benefits package
Responsibilities
- Define and communicate the product vision and roadmap, including agentic AI capabilities
- Own and groom a prioritized backlog across development, data, and evaluation workstreams
- Translate business needs into actionable user stories with acceptance criteria and AI quality measures
- Lead stakeholder engagement and manage expectations across leaders, customers, and delivery teams
- Partner with Scrum teams to integrate AI/ML cycles into sprint planning and reviews
- Drive value through experimentation, prototyping, and data-informed prioritization
- Make timely decisions under uncertainty, resolving blockers and balancing scope, speed, and cost
- Conduct market research and user feedback to inform AI/ML and capability trends
- Support internal communication and enablement on AI functionality and responsible use
- Monitor post-release model performance and lead continuous improvement in line with responsible AI best practices
Key requirements
- Bachelor’s degree in Business, Computer Science, Information Systems, Liberal Arts, or a related field (or equivalent practical experience)
- Typically 5+ years (minimum 3–5+) of experience as a Product Owner or similar role in Agile environments
- 2+ years of experience in financial regulatory and/or compliance domains
- Experience delivering AI, machine learning, or data-driven products, including exposure to agentic AI development
- Working knowledge of the AI/ML product development lifecycle (data collection/labeling, training/fine-tuning, evaluation, deployment, monitoring)
- Solid technical literacy across APIs, cloud services, SDLC, and modern software architecture; proficiency with Jira, Version One, Confluence
- Strong communication, collaboration, and negotiation skills across global teams
- Understanding of responsible AI concepts (safety, fairness, bias mitigation, explainability, data privacy, regulatory considerations)
- Excellent communication and stakeholder management
- Collaborative, cross-functional leadership
- Decision-making under uncertainty
- AI/ML product lifecycle
- Agentic AI development
- Data-informed decision making
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