Top Tech Jobs & Startup Jobs in Montreal

Leads advanced AI research on enterprise agentic systems, focusing on tacit knowledge, continual learning, resilience, safety, threat detection, privacy, and responsible AI. Defines research agendas, publishes influential work, validates hypotheses against deployed systems, and provides scientific leadership across research, engineering, and product teams. Requires strong software development, technical influence, and communication skills.

Owns adoption, consumption, value realization, renewals, and expansion across a complex portfolio of high-value ServiceNow customers. Leads executive business reviews, customer impact planning, risk mitigation, technical issue diagnosis, and strategic renewal conversations. The role also mentors junior CSMs, contributes to playbooks and enablement, improves internal agent practices, and translates customer deployment insights into product and operational feedback. French fluency and at least two days per week in the Montreal office are required.

Research and engineer enterprise large language models across data curation, pretraining, fine-tuning, evaluation, training, and inference. Develop and test novel AI/ML methods, build reproducible training pipelines and evaluation harnesses, optimize large-scale distributed training, and collaborate with scientists, engineers, and product managers to deliver production-ready solutions.

Leads advanced AI research on enterprise agentic systems, focusing on tacit knowledge, continual learning, resilience, safety, threat detection, privacy, responsible AI, and agent evaluation. Defines research agendas, publishes influential work, validates hypotheses against real deployments, develops production-quality research software, and provides scientific leadership across research, engineering, and product teams.

Build and deploy end-to-end GenAI and ML systems for strategic customers, including RAG pipelines, agentic workflows, evaluation harnesses, guardrails, observability, and production services. Lead AI discovery workshops, translate business problems into technical solutions, collaborate with engineers, create reusable frameworks, influence product strategy, and enable customer adoption. The role requires strong software engineering, ML, MLOps, responsible AI, platform architecture, and customer-facing delivery skills, with travel up to 30%.

Manages a network reliability and resiliency team, including career development, project prioritization, performance reviews, crisis management, and onboarding. Leads infrastructure reliability initiatives, automation efforts, process improvements, monitoring solutions, training, and adoption of new technologies. Requires hands-on Linux, database, systems, coding, cloud operations, distributed-team, SaaS infrastructure, and ITIL experience. Government of Canada Reliability Status screening is required.