Director, Enterprise AI & Machine Learning Engineering

Accountabilities:: Lead the engineering and machine learning strategy for agentic AI solutions designed to address complex needs of enterprise and retail partners. Build, mentor, and inspire high-performing engineering and science teams, fostering technical excellence, experimentation, collaboration, and strong execution. Partner directly with enterprise customers, product leaders, consultants, data scientists, machine learning engineers, and forward-deployed engineers to translate complex business challenges into impactful AI products. Guide the development of production-ready systems combining machine learning, data, software engineering, and agentic AI capabilities, with a focus on reliability, scalability, usability, and measurable customer value. Establish technical direction in a zero-to-one product environment while balancing long-term strategy with rapid experimentation, early deployments, and changing customer requirements. Lead teams through the complete product development lifecycle, from identifying customer needs and evaluating emerging technologies to building, deploying, and scaling AI systems. Represent the Enterprise AI function across the organization by communicating technical tradeoffs, progress, risks, opportunities, and strategic priorities to senior stakeholders. Build alignment across technical, product, commercial, and customer-facing teams around AI strategy and execution. Create clarity and momentum in an evolving environment while maintaining high standards for quality, responsible AI development, and customer impact. Make thoughtful decisions amid ambiguity and continuously adapt technical and product approaches based on customer feedback, business needs, and emerging technologies. Requirements: Demonstrated experience building and deploying agentic AI, generative AI, or machine learning products in production environments. Experience leading engineering, machine learning, data science, or applied science teams through product development and delivery. Proven ability to partner with product, business, customer-facing, and technical stakeholders to define requirements and deliver solutions to complex problems. Strong understanding of machine learning development practices, software engineering principles, data systems, and the operational requirements involved in scaling AI applications. Demonstrated ability to set technical direction, prioritize initiatives, manage ambiguity, and consistently deliver results in rapidly changing environments. Deep technical expertise in agentic systems, large language models, machine learning platforms, or related areas of applied artificial intelligence is preferred. Experience delivering applied machine learning products at significant scale, including solutions used by external customers or business partners, is preferred. Experience leading cross-functional initiatives spanning engineering, machine learning, data science, product, consulting, and customer-facing teams is preferred. Experience working directly with retailers, commerce platforms, or other enterprise customers to translate operational challenges into technology solutions is preferred. Proven ability to create clarity and momentum in zero-to-one environments while maintaining strong standards for quality, responsible development, and customer value. Strong communication, leadership, collaboration, strategic thinking, and decision-making skills. Benefits: Base salary range of $313,000–$330,500 CAD for Canadian-based candidates. Compensation may vary based on location, experience, skills, qualifications, and other relevant factors. Eligibility for a new-hire equity grant. Eligibility for annual equity refresh grants. Competitive compensation and benefits package. Flexible work environment allowing employees to work from home, an office, or another preferred location, subject to applicable policy. Regular opportunities for in-person connection and team-building. Additional benefits available based on work location.