Jobs at Vooban Inc.

Coordinate marketing events across Canada, the United States, and internationally, including logistics, vendors, sponsorships, budgets, inventory, staffing, and on-site execution. Coordinate three Impact IA conference editions, represent Vooban, support sales teams, capture leads in HubSpot, and measure event performance. Recommend future event investments and develop creative activations. The role requires regular Montreal office presence, travel, evening work, bilingual communication, and a valid driver’s license and passport.

Gère simultanément plusieurs projets, équipes, échéanciers, budgets, risques et changements. Coordonne les Team Leads, architectes et clients, assure la planification, le suivi de la performance, la reddition de comptes et le respect des engagements. Le poste exige du leadership, une excellente communication, l’utilisation de Confluence et Jira, ainsi qu’une expérience importante en gestion de projets, programmes et portefeuilles.

Build and deliver AI proof-of-concepts from end to end, primarily involving LLMs, agents, data extraction, workflow automation, computer vision, and IoT. Partner with sales and presales teams on client calls, clarify business needs, assess ROI, define scopes, explain technical capabilities, and identify project risks. Manage multiple POCs independently while communicating complex AI concepts clearly to technical and business audiences.

Développer et lancer des produits IA agentiques, notamment des systèmes multi-agents, outils d’automatisation du développement logiciel et plateformes d’orchestration. Concevoir des architectures robustes et scalables, intégrer des APIs et services externes, industrialiser les workflows, contribuer à la mise en production et optimiser les performances, coûts et délais d’exécution. Participer aux pratiques DevOps, CI/CD, observabilité, sécurité et décisions d’architecture en collaboration avec les équipes produit et techniques.

Conçoit, développe et maintient des pipelines de données robustes et évolutifs. Intègre des données provenant d’API, bases de données, fichiers et Kafka, puis collabore avec les équipes IA, BI et RO. Assure la qualité, les tests, la documentation, le versionnement et le déploiement du code avec Git/GitLab et CI/CD. Agit comme référence pour la structure et la provenance des données et contribue à la mise en production des solutions.

Develops and delivers AI solutions for diverse client projects, including data exploration, model selection, training pipelines, cloud and edge deployment, and result visualization. The role covers machine learning, deep learning, RAG, LLMs, NLP, computer vision, and robotics. The AI Scientist owns projects end to end, manages timelines and budgets, collaborates with experts, and advises clients in French and English.

Lead the technical direction of data engineering projects by designing scalable architectures, coaching data engineers, translating business needs into technical decisions, and contributing to critical code. Ensure delivery quality through testing, code reviews, validation, CI/CD, version control, and production deployment. Collaborate with AI, operations research, BI, and stakeholder teams while promoting effective use of AI tools and continuous team development.

Build Vooban’s enablement function from scratch for internal teams and client-facing teams. Responsibilities include creating product reference materials, technical onboarding and deployment playbooks, sales curriculum, demo and architecture libraries, banking security and compliance materials, support troubleshooting paths, and a self-service knowledge base. The role also defines strategy, operating models, metrics, product-release enablement cadence, and eventually recruits and leads an enablement team.

Owns cross-functional operational initiatives from research through completion, prepares executive and board materials, maintains OKRs and dashboards, improves CRM and account-health data, automates recurring processes, and analyzes business data. The role also coordinates commitments across Client, Product, Sales, Marketing, and Finance teams, conducts market and vendor research, and supports team growth in a startup or scale-up environment.

Lead executive conversations to identify business challenges, develop long-term technology visions and transformation roadmaps, build ROI-focused business cases, and lead complex RFP/RFI responses and proofs of concept. Advise clients on AI, BI, software, modernization, and digital transformation while partnering with sales, technical experts, and delivery teams to shape enterprise solutions and account strategy.

Lead the technical direction of AI projects, selecting suitable technologies, designing scalable and resilient solutions, and overseeing data and model deployment pipelines. Mentor AI scientists, promote coding quality and best practices, anticipate technical risks, optimize performance, and facilitate knowledge sharing. The role requires regular access to offices in Quebec City or Montreal within a hybrid work model.

Defines client product and project vision, documents business processes and needs, facilitates workshops, designs solutions with designers, prioritizes backlogs, writes user stories, aligns roadmaps with budgets and expectations, and supports production launches. The role requires bilingual French-English communication, client advisory skills, leadership, analytical thinking, and at least five years of experience, preferably in an Agile environment.

Conçoit et anime des ateliers clients, cartographie les workflows et identifie les occasions d’agentisation. Définit le context engineering, les stratégies de déploiement et les adaptations techniques pour des environnements principalement on-premises. Évalue les options d’architecture avec les développeurs et les clients, accompagne l’adoption par la formation et le coaching, mesure l’impact des déploiements et alimente le backlog produit. Le rôle exige une forte capacité technique, une expérience client complexe, une excellente communication bilingue et une aisance avec l’ambiguïté.

Develop and maintain critical software systems, using AI-assisted coding while owning architecture, monitoring, reliability, performance, security, integrations, and incident prevention. Diagnose root causes, anticipate failures, resolve production issues, reduce technical debt, and continuously improve system health. Collaborate closely with the team to deliver dependable solutions and ensure clients can rely on the systems.

Provide Level 1 and Level 2 technical support to employees through Slack, email, and Jira. Diagnose workstation, printer, network, and access issues; manage Mac devices and MDM; administer Google Workspace and internal tools; support cloud and UniFi environments; assist with endpoint security; document solutions; and contribute to IT infrastructure improvements and AI-enabled workflows.