At Keyrus, we help organizations move from experimental AI to industrialized AI, from isolated agents to orchestrated systems, and from insight to execution. This is the discipline we call being an Architect of Intelligence. Designing the Operating System of the intelligent enterprise, where intelligence is embedded into the core of business processes to create sustainable value: we operationalize intelligence. Powered by our proprietary Human Orchestrated Model™ (HOM), we architect reliable: • Intelligence Foundations, • Human in Command governance, • and Performance Steering, To create intelligent environments where technology amplifies human capabilities and performance compounds over time. With 30+ years of expertise and 2,800 employees across 28 countries, we help organizations go beyond transformation: to build adaptive, resilient, and continuously improving intelligent organizations. AI does not transform businesses. Architected intelligence does.
Hybrid · Toronto
Architect and deliver production-ready enterprise AI solutions, including agentic workflows and RAG pipelines. Collaborate with executives to translate business objectives into scalable AI capabilities and mentor junior engineers.
Remote · Toronto, Ontario, Canada
As a Forward Deployed AI Engineer, you will co-create solutions with stakeholders and translate use cases into production-ready AI solutions. You will prototype, test, deploy, and improve solutions in real client environments while ensuring they are documented and transferable.
Remote · Montreal, Quebec, Canada
As a Forward Deployed AI Engineer, you will co-create solutions with stakeholders and translate use cases into production-ready AI solutions. You will prototype, test, deploy, and improve solutions while ensuring they are documented and transferable.
Hybrid · Toronto
Design and own end-to-end data architectures and roadmaps, specifically focusing on scalable lakehouses and pipelines using Microsoft Fabric. Provide technical leadership to cross-functional teams and collaborate with clients to translate business objectives into technical implementations.
Hybrid · Toronto
Architect modern data ecosystems and end-to-end platforms using Microsoft Fabric to transform raw information into scalable intelligence. Provide technical leadership and mentorship to delivery teams while translating business objectives into strategic data roadmaps.
Hybrid · Toronto
Architect enterprise AI strategies and target-state architectures for Agentic and Generative AI solutions. Lead executive discovery initiatives and develop AI governance models to move organizations from experimentation to operational adoption.
Hybrid · Toronto
Define end-to-end AI strategies and transformation roadmaps, including maturity assessments and use-case prioritization. Design target-state architectures for generative and agentic AI while providing governance and adoption recommendations.
Hybrid · Toronto
Own the end-to-end delivery of AI-driven solutions, from business analysis and architecture to production rollout. Lead the development of agentic AI systems and mentor engineers while contributing to pre-sales and technical standards.
Hybrid · Toronto
Architect and deliver production-ready enterprise AI solutions, including agentic workflows and RAG pipelines. Collaborate with executives to translate business objectives into scalable AI capabilities and mentor junior engineers.
Hybrid · Toronto
Design and maintain enterprise-grade Power BI dashboards and Databricks data pipelines within a medallion-style architecture. Perform QA validation and troubleshoot production issues to ensure reliability and trust in reporting outputs.
Hybrid · Toronto
This leadership role involves collaborating with clients to translate business needs into effective data solutions while leading end-to-end delivery of data initiatives, including designing and optimizing scalable data pipelines and architectures. The consultant will also be responsible for defining architectural patterns, providing governance across multiple engagements, and leading the scaling of the data engineering practice.
