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.