Principal Product Manager - AI Native
New
J
JobgetherFintech, E-commerce
CanadaFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- French and English
- Experience
- 5 ans ou plus
- Required Skills
- SQLArtificial IntelligenceData AnalysisMachine LearningProduct ManagementGenerative AI
Requirements
- 5+ years of experience in product management, including responsibility for AI-native products and model-driven systems in production.
- Practical experience with generative AI tools, prompt engineering, evaluation testing, and LLM prototyping.
- Experience managing the AI model lifecycle, including problem definition, signal design, evaluation metrics, monitoring, and retraining strategies.
- Experience putting predictive systems, anomaly detection platforms, or automated decision infrastructures into production.
- Excellent mastery of SQL and experience with large transaction datasets.
- Experience with pricing systems, financial reporting platforms, market intelligence tools, or reconciliation frameworks.
- Deep understanding of digital platform economic mechanisms, pricing strategy, and revenue generation.
- Exceptional ability to explain complex technical concepts to technical, financial, and commercial teams.
- Fluency in French and English required to collaborate with international teams and stakeholders.
- Prior experience in data science, engineering, or a highly technical environment is an asset.
- Experience in travel, fintech, advertising, or other high-volume transactional environments is an advantage.
Responsibilities
- Define the product vision and roadmap for intelligent systems supporting large-scale commercial operations.
- Drive the end-to-end product strategy for price intelligence, supplier performance, and financial reconciliation systems.
- Design and scale benchmarking pricing systems using predictive modeling, elasticity signals, and real-time anomaly detection.
- Develop solutions to transform transaction data into automated performance metrics and business diagnostics.
- Establish reliable financial data pipelines covering revenue, margins, commissions, and transactions.
- Design evaluation and monitoring frameworks for AI models, including drift detection.
- Implement automated reconciliation and proactive financial inconsistency detection systems.
- Collaborate with engineering, data science, finance, and commercial teams to deliver integrated production-ready infrastructure.
- Prioritize product features, measure impact, and ensure data-driven continuous improvement.
- Communicate complex product requirements and results to diverse technical and business stakeholders.
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