Top Tech Jobs & Startup Jobs in Montreal

Build and scale first-line risk control monitoring systems using statistical analysis, automated workflows, and reusable data science modules. Define risk metrics, investigate control performance, establish thresholds and guardrails, and translate analyses into monitoring applications. Partner with risk, compliance, product, and engineering teams to improve governance, identify monitoring gaps, and support decision-making. Lead ambiguous, cross-functional initiatives while communicating findings, limitations, and recommendations to technical and executive stakeholders.

Lead complex security incident investigations from assessment through recovery, coordinating containment, remediation, evidence preservation, and stakeholder communication. Analyze threats across endpoint, identity, cloud, SaaS, network, and application environments. Build code, queries, automation, and AI-assisted workflows to improve evidence collection, detection, case management, and response. Lead post-incident reviews, drive lasting improvements, mentor responders, and participate in the incident response on-call rotation.

Build AI-enabled automation tools that simplify People Team processes and improve employee experience. Partner with People leaders to identify and prioritize opportunities, redesign workflows, develop reliable integrations, and measure outcomes using data and feedback. The role requires process improvement, software and automation experience, technical fluency across systems and data, strong UX instincts, and the ability to communicate tradeoffs and impact to senior stakeholders.

Design and maintain data architecture and pipelines to support compliance and risk teams. Build and optimize data models, standardize metrics, and create data dictionaries. Implement data quality, lineage monitoring, AI-driven agents for false-positive reduction and automation, and participate in on-call rotations to ensure SLAs are met.

Analyze workforce, talent, organizational health, and employee experience data to support senior People leaders. Build dashboards, reports, and scalable insight products; use AI to automate analyses; translate ambiguous questions into recommendations; create executive-ready storytelling; improve data quality and self-service reporting; and partner with People, data, and systems teams while protecting sensitive employee information.

Own third-party risk management and business continuity programs while building production data pipelines, integrations, policy-as-code controls, continuous monitoring, and agentic AI workflows. The role requires defining technical direction, integrating imperfect data sources, automating evidence collection, and partnering across Security, Procurement, Resilience, and Engineering teams to improve governance and operational resilience.

Lead data modeling and ownership of critical pipelines supporting Block’s product data foundation. Build reliable, governed, and monitored datasets, data quality and lineage systems, experimentation infrastructure, and AI-assisted automation. Partner with product and engineering teams to translate business needs into end-to-end data solutions, participate in on-call support, and maintain pipeline SLAs.

Own the full enterprise sales cycle for Block’s commerce and payments portfolio, from prospecting and account strategy through negotiation, contracting, launch, and expansion. Build executive relationships with global brands, develop commercial strategies, negotiate complex agreements, coordinate cross-functional teams, and deliver revenue targets. Translate market and customer insights into product and go-to-market feedback while managing strategic pipelines and opportunities.

Build infrastructure and tooling for AI evaluation, including distributed execution, task-set validation, graders, human-review calibration, statistical reporting, online feedback loops, and offline-to-online analysis. Partner with product, engineering, data, and ML teams to create reliable evaluation workflows that support faster, statistically sound AI product decisions.

Graduate research interns will own end-to-end projects to build customer world models and proactive intelligence: developing representation learning, foundation model, RL/agentic methods, evaluation frameworks, and shipping research into production to improve customer decision-making.