Top Tech Jobs & Startup Jobs in Toronto

The Associate Salesforce Engineer drives technical implementations on the Salesforce platform, collaborates with teams, and contributes to solution development and documentation.

This role involves managing a team of AI and Applied Research professionals, driving the production of AI solutions, and collaborating with product leaders to shape an AI-driven roadmap.

As a Lead Software Engineer, you will design AI-driven backend systems for accounting, integrating LLMs, ensuring performance and security, and collaborating with teams on AI solutions.

The Senior Product Manager will lead product strategy for an AI-powered tax advisory platform, enhance customer value, and collaborate across departments.

As a Staff Software Engineer, you'll design scalable backend services, oversee architecture decisions, optimize performance, and enhance CI/CD processes while collaborating with teams.

The Principal Engineer will design scalable backend services and APIs, optimize performance, and improve developer experience while collaborating with AI/ML experts and legal specialists.

The Staff Software Engineer will lead the design and implementation of the ingestion and indexing pipeline for a search platform, ensuring operational health and scalability while leveraging distributed systems and AI technology.

The role involves leading the design and delivery of a search platform's API and cloud infrastructure, focusing on providing self-service capabilities to internal clients. Responsibilities include API ownership, cloud infrastructure management, reliability engineering, and technical leadership.

The CPQ Lead Solution Engineer will drive engineering strategy and implementation of CPQ solutions, provide technical leadership, collaborate with teams, and ensure system stability.

The Senior Applied Scientist will design, build, and deploy AI solutions for document understanding in the legal domain, leveraging NLP and deep learning methodologies. This role involves collaborating with product teams, advancing model capabilities, and ensuring robust training and evaluation methodologies.