Top Tech Jobs & Startup Jobs in Montreal

Onboard clients by configuring workflows, monitor document collection and infrastructure pipelines, validate workflow performance, and improve internal processes for scalable reporting and consistent client outcomes. Collaborate with product, engineering, and client strategy teams to enhance operational workflows and platform value.

Staff Backend Engineer responsible for architecting and building scalable Python backend infrastructure, APIs, data models, document ingestion pipelines, event-driven processing systems, and AI extraction integrations. The role sets technical direction, makes architectural decisions, collaborates with customers on product development, establishes engineering best practices, and mentors backend engineers while helping build a high-performing team.

Build and lead across Tetrix’s SaaS product, data pipelines, AI agents, and telemetry infrastructure using Python and JavaScript. Set technical direction, make architectural decisions, shape product strategy, collaborate with clients, establish secure and scalable engineering practices, mentor engineers, and help build a high-performing team.

Build and own production AI/ML systems for private-market data, including agentic document retrieval, extraction and normalization pipelines, validation, audit trails, and portfolio analytics. Shape AI strategy, model selection, evaluation frameworks, and product direction. Collaborate with clients, support customer-facing initiatives, establish engineering standards for secure and scalable B2B SaaS, and mentor future team members.

The Finance & Operations Analyst validates financial data, enhances data processes, collaborates across teams, and develops client partnerships in a startup environment focused on alternative markets.

Build and scale backend systems for a B2B SaaS platform, including data pipelines, AI agents, telemetry and document/data extraction; contribute to product direction, work with clients, champion best practices, and mentor team members.

Build and improve AI/ML systems and data pipelines for a B2B SaaS platform; shape product and technical strategy; work with customers; mentor team members; ensure secure, robust, and scalable infrastructure.

Build and maintain the SaaS product, data pipelines, AI agents, and telemetry; contribute to product and tech strategy; work with customers; set engineering best practices and mentor teammates.