Top Tech Jobs & Startup Jobs in Toronto

Drive execution of product initiatives, manage AI product health metrics, foster cross-functional collaboration, and tackle ambiguous challenges effectively.

Own and execute the core platform roadmap for APIs, data, identity, and integrations. Define technical requirements, partner with engineering and product teams, monitor platform metrics, manage risks and dependencies, and produce documentation and enablement to drive adoption, scalability, security, and reliability across the Caseware Cloud ecosystem.

Own global paid media strategy and optimization across search, social, display, and programmatic. Lead North America execution, apply AI-driven solutions, manage six-figure budgets, run A/B tests, oversee audience segmentation and tracking, collaborate with content, product, and sales, deliver performance reporting, and optimize ABM campaigns to drive leads, pipeline, and ROI.

Design, develop, and maintain audit engagement content, methodologies, and automated workflows for Caseware's cloud audit products. Translate U.S. auditing standards into scalable software solutions, create templates and workpapers, support testing and UAT, collaborate with product, engineering, and QA, and research standards and automation opportunities to improve audit quality and efficiency.

Manage end-to-end technical recruiting for Engineering, Product, Data, and AI teams: build pipelines, source and screen candidates, coordinate interviews and offers, leverage ATS and AI recruiting tools to improve hiring velocity and candidate experience, and partner with hiring managers and People Operations for onboarding.

The Instructional Designer will create and manage engaging e-learning content, collaborating with teams and utilizing various authoring tools and LMS.

The Product Manager will oversee AI capabilities development within Caseware, shaping priorities, requiring technical fluency, and ensuring quality through evaluation frameworks and collaboration with domain experts.

The Product Analyst will oversee product analytics, collaborate with teams, define metrics, build dashboards, and improve data quality in a hybrid work environment.

Lead architecture and delivery of an AI-ready data platform: define enterprise data models, medallion/lakehouse patterns, data governance, observability, secure interoperability, and mentor teams to build production-ready AI data products.

Lead design and delivery of an AI-ready, AWS-native enterprise data platform and lakehouse. Define architecture patterns, modeling standards, ingestion/CDC, observability, governance, and secure interoperability. Mentor teams, contribute hands-on to platform modernization, enable vector/RAG AI workflows, and provide reference implementations to drive consistent, scalable data products and analytics.