Managing Director of Technology

Accountabilities:: Lead technical delivery for enterprise clients, serving as the senior technical authority on major engagements, evaluating feasibility, defining architecture, and ensuring solutions are successfully delivered. Develop scalable delivery systems and processes, including discovery frameworks, reference architectures, deployment templates, evaluation practices, staffing models, and repeatable approaches that enable multiple engagements to operate effectively. Hire, lead, and develop the engineering organization, setting technical standards, managing the talent pipeline, providing architecture guidance and code review, and helping engineers grow through direct and constructive feedback. Own platform and infrastructure direction, making decisions around build versus buy, tooling, deployment, security, and architectural priorities while partnering with engineering leadership on day-to-day execution. Shape AI technology strategy through hands-on experience with LLM orchestration, RAG, agents, evaluation, fine-tuning, and other emerging technologies, prioritizing technical investments based on practical client value. Partner closely with senior leadership on business and technical strategy while maintaining ownership of technical execution, engineering capability, and the platform. Engage directly with client executives and technical stakeholders, translating complex technical trade-offs into clear recommendations and decisions. Contribute hands-on when necessary, helping resolve production issues, unblock teams, and maintain technical depth across critical projects. Requirements: 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. Benefits: Remote-friendly position available across Canada. Independent contractor arrangement for Canadian applicants. Preference for candidates aligned with the EST timezone. Periodic travel of approximately 10–20% for client work, team offsites, and industry events. Opportunity to lead and shape a growing technical organization, including its engineering team, delivery model, systems, and technical direction. Exposure to production AI systems, enterprise technology challenges, and complex client engagements. Inclusive, collaborative environment that values diverse perspectives and high-performing teams.