Top Tech Jobs & Startup Jobs in Montreal

The Staff Backend Engineer is responsible for designing and developing AI platforms, backend services, and APIs, ensuring scalability and reliability while collaborating with cross-functional teams and mentoring engineers.

Lead learning operations and enablement, manage LMS and vendor relationships, drive learning governance and AI-enabled innovation, oversee compliance training, measure learning impact, and coach a team of instructional design and operations professionals to deliver scalable enterprise learning aligned to business priorities.

The Senior Staff SRE leads reliability engineering initiatives, drives operational excellence, mentors staff, and influences architecture to enhance system reliability and performance.

Lead architecture and delivery of large-scale, cross-team software systems. Design and implement AI/LLM multi-agent workflows, define CI/CD and testing strategy, resolve cross-team architectural bottlenecks, mentor engineers, and coordinate large programs to ensure scalable, reliable, and cost-effective solutions.

As a Software Engineering Manager, lead multiple software engineering teams, guide best practices, drive innovation, and support career development while collaborating with product management.

The role involves designing and developing high-performance web apps, improving user interfaces, maintaining component libraries, and ensuring code quality through comprehensive testing and collaboration with other teams.

Design, develop, and maintain scalable, high-performance web applications and shared component libraries. Implement automated testing and CI/CD, improve scalability and reliability, troubleshoot production incidents, provide live-site support, own cross-team projects, and collaborate with Product and Design to deliver accessible, performant user experiences for fleet-management platforms.

Design and build scalable, semantically consistent 360 entity data models and transformation pipelines. Implement cleansing, enrichment, KPIs, scoring, and business rules in SQL and Python/Scala, ensure data quality, lineage, and performance at scale. Use AI coding assistants and SDD to accelerate development, create tests and documentation, and collaborate with domain experts, data scientists, and product teams to deliver trusted, reusable data assets.

Lead Data Acquisition Team, drive AI-augmented development, establish specification-driven methodology, oversee data pipeline architecture and ensure operational excellence.