EnStream is a trusted leader in secure mobile identity verification and digital trust in Canada. We work at the intersection of technology, telecommunications, data, and identity to enable organizations to deliver seamless, secure digital experiences to their customers. Jointly owned by Canada’s largest telecom providers, EnStream is uniquely positioned to provide secure access to mobile network insights that drive growth, reduce fraud, and protect consumers. We believe that earning trust is the foundation of every excellent customer relationship. And we’re building the technology, intelligence, and partnerships to make that possible at scale. We are seeking a high-impact Lead Product Manager
- AI & Trust Intelligence to own and lead the development of AI-powered data products across EnStream Trust Platform, our mobile identity and trust intelligence platform. This role is pivotal in defining how EnStream transforms authoritative mobile network, device, SIM, account, and identity signals into intelligent products that help enterprises make better decisions across onboarding, authentication, account protection, transaction monitoring, and fraud prevention. You will lead initiatives across AI-powered trust scoring, fraud risk intelligence, anomaly detection, model explainability, decisioning workflows, and customer-facing insights. You will partner closely with engineering, data science, sales, product, and enterprise customers to build intelligence to enables trust at scale. Define and own the product strategy for AI and Trust Intelligence products, including trust scores, risk signals, decisioning models, model outputs, reason codes, and customer-facing insights. Build a cohesive multi-year product roadmap aligned to business priorities, carrier data capabilities, enterprise customer needs,



fraud trends, and evolving regulatory expectations. Drive the vision for next-generation mobile identity intelligence, including AI-powered fraud detection, adaptive risk scoring, identity reputation, signal intelligence, and real-time trust decisioning. Trust Intelligence & AI Model Productization Lead the development of AI/ML-powered trust data and intelligence products, supporting orchestration across signals, rules and models. Productize AI models into practical enterprise offerings, including APIs, batch outputs, dashboards, reports, decision engines, and workflow integrations. Define customer-facing score interpretation, reason codes, confidence indicators, and model explainability requirements. Co-establish product metrics for model performance and customer value, including precision, recall, false positive rates, lift, stability, drift, coverage, conversion impact, fraud reduction, and operational efficiency with Data and AI partners. Build processes for continuous model improvement using customer outcomes, feedback data, fraud signals, and partner insights. Lead discovery sessions that translate customer problems into AI product opportunities, pilot designs, and measurable success criteria. Design proof-of-value programs that demonstrate the impact of AI and trust intelligence data products. Partner with GTM, Sales, and Solutions Engineering to support enterprise adoption, customer success,



and product-led growth. Develop clear product narratives, demos, use case playbooks, and technical explanations that make AI outputs understandable and actionable for business, fraud, risk, and technology stakeholders. Work with carrier partners and strategic data providers to identify opportunities to deepen signal coverage, data quality, and product differentiation. Responsible AI, Privacy & Compliance Alignment Ensure AI product capabilities are explainable, auditable, measurable, and appropriate for high-trust enterprise environments. Partner with privacy, legal, security, data governance, and AI governance teams to ensure AI capabilities are developed with privacy-by-design and secure-by-design principles. Maintain alignment with applicable privacy, identity, fraud, and risk management expectations, including PIPEDA, data governance requirements, AI governance, customer contractual obligations, and emerging responsible AI practices. 6-8+ years of product management experience in AI/ML products, data products, fraud/risk, digital identity, cybersecurity, fintech, telecom, enterprise SaaS, or decisioning platforms. ~ Experience working closely with data science, machine learning, data engineering, software engineering, architecture, privacy, and security teams. ~ Experience taking AI, analytics, scoring, or data products from discovery through production launch and ongoing optimization. ~ Familiarity with model development workflows, including feature engineering, labels, training data, evaluation metrics, monitoring, feedback loops, and model governance. ~ Experience with fraud prevention, identity verification, digital onboarding, authentication, account takeover, synthetic

📌 Lead Product Manager (Toronto)
🏢 EnStream
📍 Toronto