Top Tech Jobs & Startup Jobs in Montreal

Manage cloud and IT projects from planning through delivery using Agile methodologies. Responsibilities include developing project plans, managing scope, schedules, budgets, risks, issues, backlogs, and client communications. The role requires facilitating customer discussions, maintaining project reporting and compliance, driving business outcomes, and supporting cross-functional initiatives while building strong client relationships.

Build and deliver production-grade AI applications, automations, and cloud-native systems within client environments. Own assigned workstreams end-to-end, translate ambiguous problems into scoped solutions, contribute to discovery and architecture sessions, identify risks, and transfer durable capabilities to clients. Forward Deployed Engineers collaborate with technical and business stakeholders, prototype rapidly, document reusable patterns, and may support AI enablement programs across functions such as Finance, HR, Legal, and Supply Chain.

Lead a team of software engineers and architects delivering complex, AI-first cloud applications for enterprise clients. Responsibilities include people management, requirements gathering, architecture, backlog ownership, technical decision-making, AI-driven testing, client discovery, risk escalation, executive communication, mentoring, and pre-sales support. The role requires hands-on AWS cloud-native development, consulting expertise, and leadership across large, multi-stakeholder engagements.

The Senior Forward Deployed Engineer manages client relationships, architecting, building, and closing deals while ensuring autonomous delivery of AI solutions. Responsibilities include discovery, architecture reviews, and capability transfer to clients, requiring significant engineering and client-facing experience.

Lead the architecture and implementation of complex cloud-based data solutions for clients. Define strategic data roadmaps, support pre-sales engagements as a data engineering subject matter expert, conduct technical interviews, mentor architects and engineers, and establish data standards and operating procedures. The role requires extensive AWS and complex data systems experience, expertise across traditional and modern data technologies, strong documentation practices, and excellent communication.

Design and implement enterprise contact center transformations using Amazon Connect, generative AI (Bedrock/Claude), serverless backends, and full-stack React tooling. Build contact flows, AI agents, CDK infrastructure, observability, CI/CD and migration solutions; collaborate with customers, mentor engineers, and ensure production reliability, security, and accessibility.

The AI/ML Engineering Manager leads ML engineering teams, manages client engagements, shapes architecture, ensures technical quality, and drives business growth through ML operations.

Lead architecture and delivery of AI-native Amazon Connect contact center solutions: design multi-agent conversational AI, implement contact flows and serverless backends, author IaC, build analytics and observability, mentor engineers, and manage risk and client engagements for production contact centers.

Lead change strategy and stakeholder engagement for technology and AI-enabled transformations. Design and execute adoption programs, define adoption metrics, monitor readiness and risks, and apply human-centered change frameworks. Support AI adoption, workforce impacts, and delivery excellence while partnering with clients, analytics, and product teams to link behavior change to business outcomes.

Lead the product workstream in client engagements to assess current PDLC, design future-state AI-native product development, coach PMs, scope and write executable specs for prototypes and MVPs, shape agentic product tooling, and feed field learnings back into methodology and pre-sales.