Top Tech Jobs & Startup Jobs in Montreal

The Enterprise Solutions Manager drives operational excellence and client success through strategic analysis, process optimization, and project management, collaborating with various teams to deliver AI solutions.

Manage relationships with strategic healthcare clients, oversee complex projects, innovate operational processes, and lead large teams to improve AI training and application.

Leads operational delivery for complex enterprise AI engagements, aligning commercial, engineering, and executive client stakeholders. Owns multi-workstream execution, agile delivery ceremonies, requirements scoping, risk mitigation, KPI and ROI analysis, process design, and business cases. Partners with technical leads on strategic deployments, structures ambiguous challenges into scalable frameworks, advises senior clients, and mentors Enterprise Solutions Managers and delivery teams.

Leads enterprise client engagement, solution design, operational process creation, cross-functional project delivery, workflow optimization, team reviews, staff mentoring, performance analysis, and real-time analytics initiatives. The role bridges enterprise clients, global talent, and internal product, engineering, and operations teams while building scalable processes and supporting the launch of a next-generation marketplace.

The Enterprise Solutions Specialist drives client success through project management and operational oversight, ensuring scalable processes and effective communication between teams. This role involves direct client engagement and supports automation initiatives.

Work directly with clients to scope, prototype, and deploy AI-powered workflows. Build scalable systems using LLMs, embedding and retrieval systems, and backend infrastructure. Translate messy data and operational constraints into production-ready solutions, iterate with stakeholders, and maintain deployed systems (including on-call support).

Lead end-to-end AI solutions as a forward-deployed engineer: scope, design, and deploy ML/LLM systems; partner with clients and stakeholders; build infrastructure, data pipelines, and reusable platform components; mentor engineers; own projects from discovery through production and provide on-call support.

Lead high-impact AI solutions, overseeing architecture and deployment. Partner with stakeholders, coach engineers, and drive project success from inception to launch.