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We are looking for an experienced Product Manager to lead AI-driven product initiatives. This Long-term Contract opportunity is ideal for a strategic and detail-oriented individual who can connect business goals with practical product execution while guiding ideas from discovery through launch and ongoing optimization. The role requires close coordination across stakeholders, data teams, and technical partners to deliver reliable, usable, and well-governed AI capabilities.
Job Responsibility
Shape business objectives into a clear AI product roadmap, including prioritized use cases, delivery milestones, and measurable outcomes
Lead the full product lifecycle for AI-enabled features, from early concept development and testing through production deployment and refinement
Establish detailed product criteria related to data inputs, model performance, transparency expectations, and operational controls
Rank initiatives and backlog items by weighing organizational impact, readiness of supporting data, and implementation complexity
Direct experimentation efforts by defining success measures, reviewing results, and adjusting product direction through iterative learning
Partner with cross-functional teams to maintain strong governance practices, including traceability, risk awareness, bias reduction, and audit readiness
Oversee critical data dependencies by aligning on sourcing, access, quality standards, and lineage requirements needed for successful delivery
Evaluate completed work based on output reliability, business usefulness, and readiness for end-user adoption
Track live product performance, including consistency, model drift, and user adoption trends, and drive continuous improvements over time
Requirements
10+ years of hands-on experience in product management, project management, or operations-focused delivery roles
Demonstrated success delivering AI-enabled products or features from planning through release and ongoing enhancement
Strong understanding of AI concepts, model evaluation approaches, and iterative product development methods
Working knowledge of data environments, including pipelines, data quality practices, governance frameworks, and controlled access
Ability to assess business value alongside technical limitations and data constraints to make sound prioritization decisions
Familiarity with governance, risk management, and explainability considerations associated with AI-based solutions
Proven ability to influence stakeholders, navigate ambiguity, and make well-reasoned decisions in complex environments
Customer-focused mindset with an emphasis on trustworthy outputs, usability, and operational effectiveness