Managing Director of Technology

This is a senior technology leadership role responsible for owning the technical organization and delivery function within a fast-growing, AI-native environment. You will lead enterprise client delivery, make critical architecture decisions, and serve as the senior technical voice with executive stakeholders. The role combines hands-on technical depth with organizational leadership, requiring you to move comfortably between production systems and C-suite conversations. You will build and develop the engineering team while creating scalable approaches to discovery, architecture, deployment, and delivery. You will also shape AI technology strategy based on practical experience with systems that operate in production. The position is remote-friendly across Canada, with a preference for EST timezone alignment and periodic travel.

• Demonstrated experience building and deploying AI/ML systems in production environments that are actively used and relied upon, rather than prototypes or demonstrations alone.
• Experience hiring and leading a technical team of at least five people, with a track record of navigating organizational growth and improving team effectiveness.
• Strong ability to communicate technical concepts, trade-offs, and architecture decisions to non-technical executives and senior stakeholders in high-stakes environments.
• Deep, hands-on understanding of AI architecture, with practical experience across areas such as LLM orchestration, RAG, agents, evaluation, and fine-tuning.
• A builder-first mindset and willingness to engage directly with technical challenges, production issues, and team obstacles rather than relying solely on delegation.
• Strong knowledge of cloud infrastructure and modern engineering practices, with the technical judgment required to make platform and architecture decisions confidently.
• Bachelor’s degree or equivalent practical experience; an advanced degree is considered an asset but is not required.
• Experience scaling a startup or early-stage organization, including building teams, systems, and operational practices, is an asset.
• Experience working within a services or consultancy model, including SOWs, staffing, and client delivery, is an asset.
• An established professional network of engineers who could potentially contribute to a growing technical organization is an asset.
• Strong accountability, curiosity, adaptability, and comfort making important decisions with incomplete information.
• Commitment to responsible AI practices, including transparency, human oversight, privacy, and thoughtful implementation.