Top Tech Jobs & Startup Jobs in Toronto

Design, build, deploy, and monitor production-grade AI and ML solutions (including GenAI/LLM applications) for Long-Term Care. Collaborate with cross-functional teams to operationalize models, implement MLOps/LLMOps pipelines, ensure governance/compliance, and improve observability, scalability, and cost efficiency. Mentor junior staff.

Provides project and process support for IT Security and Business Resilience initiatives. Responsibilities include modeling workflows, documenting SDLC and Agile processes, defining interactions between risk and support teams, assessing operational inefficiencies, and representing Risk Line 1b in project governance meetings. The role requires coordinating cross-functional teams, maintaining process documentation, supporting project governance, and helping design target-state operating models.

Supports Canada Operations through executive communications, strategic initiative coordination, employee engagement, organizational effectiveness, leadership events, and change enablement. Develops executive presentations, briefing materials, communication plans, and leadership updates; coordinates cross-functional workstreams, timelines, risks, and stakeholders; and contributes to learning, onboarding, leadership development, employee experience, and organizational culture programs. The role partners with senior leaders and the COO Office to advance enterprise priorities and deliver high-visibility communications and events.

Leads a multi-location team managing mortgage and lending delinquencies, loss mitigation, repayment solutions, and complex customer cases. Ensures regulatory compliance, risk controls, service quality, operational performance, and team development. Partners with Lending, Risk, Legal, Customer Experience, and Operations teams while supporting process improvements, transformation initiatives, audits, and data-driven enhancements.

Design, develop, and support cloud-native trading, analytics, and risk-management applications on Azure. Integrate market data and AI/ML capabilities, maintain CI/CD pipelines, collaborate with product and business stakeholders, and drive Agile engineering best practices to deliver scalable derivatives technology.

Owns the vision, prioritization, backlog, and delivery of insurance illustration capabilities. The role defines features and user stories, validates product and tax calculations, leads business acceptance testing, coordinates cross-functional delivery, manages risks and dependencies, and monitors post-launch outcomes. It requires collaboration with business, technology, sales, marketing, compliance, and operations teams to improve advisor and customer experiences.

Owns global digital storefront reporting and insights, including measurement plans, dashboards, KPI frameworks, performance analysis, experimentation measurement, data quality, and optimization recommendations. Partners with marketing, product, technology, engineering, and leadership teams to translate complex digital data into actionable business insights and enable self-service analytics across regions and digital properties.

Senior Business Analyst leading requirements discovery, solution design, stakeholder alignment, and troubleshooting for Adobe Experience Manager and enterprise design systems. The role translates business objectives into scalable web and mobile experiences, documents functional and accessibility requirements, supports publishing workflows, facilitates Agile ceremonies, and coordinates Marketing, Design, Engineering, QA, Accessibility, and Product teams.

Develop and lead machine learning and generative AI projects, including prompt engineering, RAG applications, LLM fine-tuning, synthetic data generation, experimentation, and cloud deployment. Clean and analyze large datasets, collaborate with data and ML engineers, define business requirements, communicate technical findings, and conduct peer and code reviews.

Develop and deploy production-grade AI, machine learning, and generative AI solutions for insurance business challenges. Responsibilities include building LLM applications, prompt engineering, RAG workflows, data pipelines, experiments, proof-of-concepts, and scalable AI systems. The role involves monitoring model performance, generating business insights, collaborating with stakeholders, and communicating technical findings to diverse audiences.