Top Tech Jobs & Startup Jobs in Toronto

Own and secure enterprise identity infrastructure across multi-cloud and SaaS environments. Architect SSO, cloud IAM policies, application permissions, and identity lifecycle automation using SCIM, APIs, and scripts. Govern third-party integrations, conduct access reviews, apply Zero Trust and least-privilege controls, implement PAM and JIT access, and monitor identity logs for anomalous activity.

Own strategy, vision, roadmaps, and execution for technically complex data, cloud, and AI products. Lead discovery through launch, define requirements and success metrics, make prioritization and build-versus-buy decisions, and partner with engineering, architecture, data, and AI/ML teams. Serve as the senior product contact for Fortune 500 clients, lead distributed delivery teams, manage dependencies and stakeholders, and mentor junior product professionals.

Own the roadmap and lifecycle of data and AI products, from enterprise discovery and problem definition through delivery, launch, and iteration. Translate business needs into product requirements, partner with engineering, data engineering, and design, define measurable outcomes, lead Agile ceremonies, prioritize feedback-driven improvements, and communicate risks and trade-offs to stakeholders. The role also contributes to product discovery, prioritization, and delivery practices.

Lead design, architecture, and delivery of enterprise-scale data platforms using Databricks and Spark. Architect Lakehouse solutions, build ETL/ELT pipelines, implement IaC and CI/CD, ensure data governance and security, mentor engineers, and partner with Fortune 500 clients from discovery through production.

The Senior Manager, Business Operations will lead contract management, support financial operations, ensure compliance, and optimize internal processes while enhancing client relations and business strategy execution.

Design, build, and scale data-driven platforms and systems, focusing on backend and frontend engineering, integrations, and AI capabilities.

The DevOps Engineer will optimize cloud computing solutions, enhance infrastructure performance, ensure high availability, and manage CI/CD tools while collaborating with development teams.

The Associate AI Engineer will assist in building AI-powered backend services, integrating APIs, and developing data pipelines while collaborating with experienced engineers and teams.

Lead design, build, and operation of cloud infrastructure, CI/CD pipelines, and platform tooling. Implement IaC (Terraform), automate deployments, troubleshoot live systems, maintain monitoring/logging, mentor engineers, set DevOps technical direction, and evaluate new tools.

Work on building production-ready agentic AI applications and the Continuum platform: agent orchestration, model routing, persistent memory, tool integrations, retrieval pipelines, guardrails, evaluation, observability, and backend/APIs. Write well-tested Python code and contribute to open-source examples and documentation.